Level 1b SRAL Algorithm Theoretical Baseline Definition

PREPARATION AND OPERATIONS OF THE MISSION PERFORMANCE

CENTRE (MPC) FOR THE COPERNICUS SENTINEL-3 MISSION

Sentinel-3 Level 1b SRAL Algorithm Theoretical Baseline

Definition

Ref.: S3MPC.CLS.PBD.003

Issue: 1.1

Date: 01/07/2019

Contract: 4000111836/14/I-LG

Customer: ESA Document Ref.: S3MPC.CLS.PBD.003

Contract No.: 4000111836/14/I-LG Date: 01/07/2019

Issue: 1.1

Project: PREPARATION AND OPERATIONS OF THE MISSION PERFORMANCE CENTRE (MPC)

FOR THE COPERNICUS SENTINEL-3 MISSION

Title: Level 1b SRAL Algorithm Theoretical Baseline Definition

Author(s): CLS

Approved by: S. Labroue Authorized by J. Bruniquel, Service Manager

Distribution: Sentinel Online

Accepted by ESA P. Féménias, ESA TO

Filename S3MPC.CLS.PBD.003 - i1r0 - S3 L1b SRAL ATBD.docx

Copyright ©2019 – CLS, CNES

All rights reserved.

No part of this work may be disclosed to any third party translated, reproduced, copied or

disseminated in any form or by any means except with the written permission of CLS and CNES

Disclaimer

The work performed in the frame of this contract is carried out with funding by the European Union.

The views expressed herein can in no way be taken to reflect the official opinion of either the

European Union or the European Space Agency.

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Changes Log

Version Date Changes

1.0 29/09/2017 First version

1.1 01/07/2019 Update with changes until PB2.49A_1.21B

List of Changes

Version Section Answers to RID Changes

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Table of content

1 INTRODUCTION ............................................................................................................................................ 1

1.1 AIM ............................................................................................................................................................... 1

1.2 BACKGROUND .................................................................................................................................................. 1

2 ALGORITHMS DEFINITION AND SPECIFICATION ............................................................................................ 3

2.1 ALT_CAL_GPR_01 - TO BUILD THE GPRW SPECTRUMS ........................................................................................ 3

2.2 ALT_CAL_GPR_02 - TO DETERMINE THE MAIN FEATURES OF THE GPRW SPECTRUM.................................................. 5

2.3 ALT_CAL_GPR_03 - TO NORMALIZE THE GPRW SPECTRUMS ................................................................................ 7

2.4 ALT_CAL_PTR_01 - TO BUILD THE PTR SPECTRUMS ............................................................................................ 8

2.5 ALT_CAL_PTR_02 – TO CORRECT THE PTR ...................................................................................................... 10

2.6 ALT_CAL_PTR_03 – TO COMPUTE THE TOTAL POWER OF THE PTR ....................................................................... 11

2.7 ALT_CAL_PTR_04 – TO COMPUTE THE GENERAL FEATURES AND THE FEATURES OF THE MAIN LOBE OF THE PTR ............ 12

2.8 ALT_CAL_PTR_05 – TO COMPUTE THE FEATURES OF THE SECONDARY LOBES OF THE PTR ......................................... 15

2.9 ALT_CAL_PTR_06 - TO COMPUTE PHASE CALIBRATION (CAL 1) CORRECTIONS (SAR MODE) ..................................... 17

2.10 ALT_CAL_PTR_07 - TO COMPUTE POWER CALIBRATION (CAL 1) CORRECTIONS (SAR MODE) .................................... 18

2.11 ALT_CAL_PTR_08 - TO COMPUTE THE AGC CORRECTION TABLE (AUTOMATIC CAL1, SAR) ...................................... 19

2.12 ALT_CON_TIM_01 - TO CONVERT THE ON-BOARD TIME COUNTERS INTO GPS TIMES ............................................... 24

2.13 ALT_CON_TIM_02 - TO REFERENCE THE TIME-TAGS TO THE MEASUREMENT ON THE OVERFLOWN SURFACE .................. 25

2.14 ALT_CON_TIM_03 - TO COMPUTE THE TIME-TAG OF C BAND MEASUREMENTS IN SAR MODE OVER A TRACKING CYCLE .. 27

2.15 ALT_COR_RAN_01 – TO COMPUTE THE INTERNAL PATH CORRECTION AND THE CORRECTED TRACKER RANGES............... 28

2.16 ALT_COR_RAN_02 – TO COMPUTE THE DOPPLER CORRECTION AND THE CORRECTED TRACKER RANGES (LRM MODE) ... 31

2.17 ALT_COR_RAN_04 - TO COMPUTE AND APPLY DOPPLER CORRECTION (SAR MODE) ................................................ 33

2.18 ALT_COR_RAN_05 - TO COMPUTE THE SLANT RANGE CORRECTION (SAR MODE) .................................................... 35

2.19 ALT_COR_WAV_01 – TO CORRECT THE WAVEFORMS FOR THE GPRW (LRM MODE) .............................................. 38

2.20 ALT_COR_WAV_02 - TO APPLY PHASE CALIBRATION (CAL 1) CORRECTIONS (SAR MODE) ........................................ 39

2.21 ALT_COR_WAV_03 - TO APPLY POWER CALIBRATION (CAL 1) CORRECTIONS (SAR MODE) ...................................... 40

2.22 ALT_COR_WAV_04 – TO CORRECT THE WAVEFORMS FOR GPRW (SAR MODE) .................................................... 41

2.23 ALT_COR_WAV_05 - TO CORRECT WAVEFORMS FROM AGC (SAR MODE) ............................................................ 43

2.24 ALT_COR_WAV_06 - TO GENERATE THE DOPPLER BEAMS (SAR MODE) ............................................................... 44

2.25 ALT_COR_WAV_07 - TO APPLY THE FINE SLANT RANGE CORRECTION (SAR MODE) ................................................. 46

2.26 ALT_COR_WAV_09 - TO PERFORM RANGE COMPRESSION (SAR MODE) ............................................................... 48

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2.27 ALT_COR_WAV_10 - TO APPLY THE COARSE SLANT RANGE AND TRACKER MISALIGNMENT CORRECTIONS (SAR MODE) ... 49

2.28 ALT_COR_WAV_11 - TO PERFORM THE DOPPLER BEAMS STACK MULTI-LOOKING (SAR MODE) ................................. 51

2.29 ALT_COR_WAV_12 - TO COMPUTE THE LRM LIKE KU AND C BAND POWER WAVEFORMS FROM SAR MODE PULSES ..... 53

2.30 ALT_PHY_BAC_01 – TO CORRECT THE AGC FOR INSTRUMENTAL ERRORS .............................................................. 57

2.31 ALT_PHY_BAC_02 - TO COMPUTE THE SCALING FACTORS FOR SIGMA0 EVALUATION (LRM MODE) ............................ 58

2.32 ALT_PHY_BAC_03 - TO COMPUTE THE SCALING FACTORS FOR SIGMA0 EVALUATION (SAR MODE) ............................. 63

2.33 ALT_PHY_LOC_01 - TO COMPUTE SURFACE LOCATION (SAR MODE) .................................................................... 68

2.34 ALT_PHY_LOC_02 - TO DETERMINE DOPPLER BEAM DIRECTIONS (SAR MODE) ....................................................... 73

2.35 ALT_PHY_RAN_01 – TO COMPUTE THE TRACKER RANGES (CORRECTED FOR THE USO FREQUENCY DRIFT) .................... 75

2.36 GEN_ENV_SUR_01 - TO DETERMINE THE SURFACE TYPE ..................................................................................... 78

3 ACRONYMS ..................................................................................................................................................79

List of Figures

Figure 2-1 Determination of slant range correction ------------------------------------------------------------------- 36

Figure 2-2 Influence of surface topography on Doppler beams location ----------------------------------------- 45

Figure 2-3 Syncronisation of Ku and C bands measurements ------------------------------------------------------- 69

Figure 2-4 Determination of surface sample locations ---------------------------------------------------------------- 71

Figure 2-5 Determination of Doppler beams directions -------------------------------------------------------------- 74

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1 Introduction

1.1 Aim

This document is aimed at defining the “scientific” algorithms used in the Level 1b processing of the

Sentinel-3 Surface Topography Mission SRAL (SAR Altimeter) data.

The definition of the altimeter Level 1b scientific algorithms, provided in this document, consists of the

identification and the description of their main functions. It will provide the reader with an overview of

the procedures and a global understanding of the algorithms.

Each scientific algorithm is defined, using the following items:

• Name and identifier of the algorithm

• Heritage (mission for which the algorithm is used or derived)

• Function

• Algorithm Definition:

Input data Output data Mathematical statement

• Accuracy (if any)

• Comments (if any)

• References (if any)

Level 1b products correspond to geo-located engineering-calibrated products, while Level 2 products

correspond to geo-located geophysical products.

“Scientific” algorithms represent the core of the processing. They are dissociated from “Data

management” algortihms, ensuring functions such as data acquisition, data selection and preparation,

units conversions, general cheks, products generation, processing management, etc., which strongly

depend on the format of the input and output data.

1.2 Background

1.2.1 Products levels

Level 1b products – issued from L1b processing - correspond to geo-located engineering-calibrated

products, while Level 2 products – issued from L2 processing - correspond to geo-located geophysical

products.

1.2.2 Delivery Delay

As far as Sentinel-3 Topography Mission is concerned, three products delivery delays are considered:

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• Near Real Time (NRT): delivered less than 3 hours after data acquisition, and mainly used for marine meteorology and ocean-atmosphere gas transfer studies

• Slow Time Critical (STC): delivered within 48 hours after data acquisition, due mainly to the consolidation of some auxiliary or ancillary data (e.g. preliminary restituted orbit data) and mainly used for geophysical studies and operational oceanography

• Non Time Critical (NTC): delivered within typically 1 month after data acquisition, due mainly to the consolidation of some auxiliary or ancillary data (e.g. precise orbit data), and mainly used for geophysical studies and operational oceanography.

1.2.3 Ancillary/Auxiliary and Dynamic/Static Data

Besides instrumental data (SRAL, MWR, GNSS), additional data are requested on input of the various

processings aimed at building user products:

• Ancillary data corresponds to data internal to the Sentinel-3 system (e.g. orbit, instrumental LUT, configuration data i.e. processing parameters)

• Auxiliary data corresponds to data exterrnal to the Sentinel-3 system (e.g. meteo fields, land/sea mask)

Both types of data may be dynamic or static:

• Dynamic data corresponds to time-varying data (e.g. orbit, meteo fields)

• Static Data corresponds to constant data (e.g. instrumental LUT, land/sea mask, configuration data)

1.2.4 Altimeter Terminology

Altimeter measurements are performed either in Low Resolution Mode (LRM) or in Synthetic Aperture

Radar (SAR) mode.

• In LRM mode, pulses are transmitted at the Pulse Repetition Frequency (PRF about 1924 Hz) rythm, following a typical pattern of 3 Ku-band pulses / 1 C-band pulse / 3 Ku-band pulses. These pulses are processed and averaged on-board to provide a power waveform (128 I2+Q2 samples) every about 50.9 ms, corresponding to the averaging of 84 Ku-band pulses and of 14 C-band pulses. This measurement is called an elementary measurement or a 20-Hz measurement. It contains Ku-band and C-band waveforms and associated parameters.

• In SAR mode, the Pulse Repetition Frequency (PRF) is about 17 800 Hz. Pulses are transmitted by a series of 66 (64 Ku-band pulses and 2 C-band pulses), called a burst, corresponding to a duration about 12.74 ms. A burst corresponds thus to a 80-Hz measurement, and contains 64 Ku-band and 2 C-band waveforms (128 I and Q samples for each of them).

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2 Algorithms Definition and Specification

2.1 ALT_CAL_GPR_01 - To build the GPRW spectrums

2.1.1 Heritage

None

2.1.2 Function

To build the Ku- or C-band GPRW spectrum (standard and oversampled) from the Level 0 Ku- or C-band I

and Q pulses of a nominal CAL2 calibration sequence.

2.1.3 Algorithm Definition

2.1.3.1 Input data

• Band of the sequence (Ku or C)

• Number of cycles in the sequence (Nc)

• For each cycle of the sequence (a cycle contains 4 bursts of 1C / 64 Ku / 1C pulses):

For each burst of the cycle :

64 Ku-band pulses (each of them consisting of 128 I and Q complex values) 2 C-band pulses (each of them consisting of 128 I and Q complex values)

• Altimeter instrumental characterization data:

Index of the 0-frequency sample

2.1.3.2 Output data

• Samples of the standard GPRW spectrum (128 I2+Q2 values) for the band (Ku or C) of the input sequence

2.1.3.3 Mathematical statement

• Building of the standard GPRW spectrums (which will be used to correct the waveforms in the Level 1b measurement processing)

Case of an input Ku band sequence:

For each of the 4*64*Nc Ku-band pulses (I and Q) of the input sequence, a 128-points FFT is

performed and the I2+Q2 spectrum is derived. The average Ku-band 128-points I2+Q2 spectrum is

then computed.

Case of an input C band sequence:

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The same process is applied to the 4*2*Nc C-band pulses (I and Q) of the input sequence.

• Removal of the potential 0-frequency spike from the 128-points Ku-band and C-band spectrums, by superseeding the 0-frequency sample by a linear interpolation of the two samples on either side

2.1.4 Comments

The Fast Fourier Transforms used in this algorithm shall be performed with zero-padding capability and

shall generate centred complex spectrums considering that the zero-frequency sample is located at

Ind_0_Freq for the standard spectrum

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2.2 ALT_CAL_GPR_02 - To determine the main features of the GPRW spectrum

2.2.1 Heritage

TOPEX/Poseidon (Poseidon-1), Jason-1 (Poseidon-2), Jason-2 (Poseidon-3).

2.2.2 Function

To compute the main features of each side (right: frequencies > 0; left: frequencies < 0) of a GPRW

spectrum (Ku band or C band) provided by the CAL2 nominal internal calibration sequence and to control

them with respect to predefined values.


2.2.3.1 Input data

• Standard GPRW spectrum :

Samples of the GPRW spectrum (128 I2+Q2 values)

• Altimeter instrumental characterization data (DAAD):

FFT step in frequency (Hz) Index of the 0-frequency sample (/)

Half width of the analysis window to compute the DC component: Predefined values of the main features (values that have been obtained by the ground

measurement of the GPRW or by the on-board GPRW taken as the reference filter for the mission)

• Configuration data (SAAD):

Thresholds percentages

2.2.3.2 Output data

Main features of the GPRW spectrums, i.e. for both left and right sides:

• Mean value of the GPRW spectrum and associated flag

• Standard deviation of the GPRW spectrum and associated flag

• Differences between the minimum and maximum values of the GPRW spectrum and associated flag

• Slopes of the linear regression of the GPRW spectrum and associated flag

• Standard deviation about the slope of the linear regression of the GPRW spectrum and associated flag


For each side of the input GPRW spectrum, the following features are computed:

• Mean of the samples • Standard deviation of the samples

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• Difference between the values of the maximum sample and the minimum sample • Slope

These features are computed for the frequency range [-, 0[ and ]0, ]. The minimum and maximum

values of each side of the GPRW spectrum are obtained and their difference is computed. Computations

are performed with values of samples expressed in dB.

The slope of each side of the GPRW spectrum is obtained from a linear regression.

The parameters given by the CAL2 calibration sequence processing to be verified are the following:

• The mean values of each of the left and right sides of the GPRW spectrum • The peak to peak amplitudes in the left and right sides of the GPRW spectrum • The slopes of the left and right sides of the GPRW spectrum

These parameters are compared with parameters issued from the reference GPRW spectrum. Ten flags

are thus obtained:

• One flag for the mean of the left side of the GPRW spectrum • One flag for the mean of the right side of the GPRW spectrum • One flag for the standard deviation of the left side of the GPRW spectrum • One flag for the standard deviation of the right side of the GPRW spectrum • One flag for the peak to peak amplitude in the left side of the GPRW spectrum • One flag for the peak to peak amplitude in the right side of the GPRW spectrum • One flag for the slope of the left side of the GPRW spectrum • One flag for the slope of the right side of the GPRW spectrum • One flag for the standard deviation of the left slope of the GPRW spectrum • One flag for the standard deviation of the right slope of the GPRW spectrum

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2.3 ALT_CAL_GPR_03 - To normalize the GPRW spectrums

2.3.1 Heritage


2.3.2 Function

To compute the normalized samples of the standard GPRW spectrums (Ku band or C band).


2.3.3.1 Input data

• Standard GPRW spectrums :

Samples of the standard GPRW spectrum (128 I2+Q2 values)



2.3.3.2 Output data

• Normalized standard GPRW spectrums :

Samples of the normalized standard GPRW spectrum (128 I2+Q2 values)

• Localization (in frequency) of the max value of the standard GPRW spectrum


For the input GPRW spectrum (standard), the normalized spectrum (values between 0 and 1) is computed

by dividing the input samples by the maximum value :

)j(VMax

)j(V)j(V

jnorm =

The frequency corresponding to the maximum value of the normalized standard GPRW spectrum is also

output for expertise purposes.

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2.4 ALT_CAL_PTR_01 - To build the PTR spectrums

2.4.1 Heritage

None

2.4.2 Function

To build 1) the Ku- and C-band power PTR spectrums (oversampled and averaged over retained pulses,

LRM/SAR modes) and 2) the Ku-band complex PTR spectrums (oversampled, from pulses of retained

bursts, SAR mode) from the Level 0 Ku- and C-band I and Q pulses of a CAL1 calibration sequence.


2.4.3.1 Input data

• Number of cycles in the sequence (N_Cycle)

• For each cycle of the sequence :

For LRM mode (14 series of 3 Ku / 1C / 3 Ku pulses):

84 Ku-band pulses (each of them consisting of 128 I and Q complex values)

14 C-band pulses (each of them consisting of 128 I and Q complex values)

For SAR mode (4 bursts of 1C / 64 Ku / 1C pulses):

For each burst of the cycle :

64 Ku-band pulses (each of them consisting of 128 I and Q complex values)

2 C-band pulses (each of them consisting of 128 I and Q complex values)


Spectrum oversampling factor (N) Number of Ku-band pulses to reject at the beginning of the LRM mode sequence (NLRM-Ku) Number of C-band pulses to reject at the beginning of the LRM mode sequence (NLRM-C) Number of Ku-band pulses to reject at the beginning of the SAR mode sequence (NSAR-Ku) Number of C-band pulses to reject at the beginning of the SAR mode sequence (NSAR-C)



2.4.3.2 Output data

• Oversampled and averaged power PTR spectrums (LRM/SAR modes):

Samples of the oversampled Ku-band PTR spectrum (128*N I2+Q2 values) Samples of the oversampled C-band PTR spectrum (128*N I2+Q2 values)

• Oversampled complex PTR spectrums (SAR mode):

• Samples of the oversampled Ku-band complex PTR spectrums (128*N I/Q values for each Ku pulses)

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A LRM mode sequence contains N_Cycle*84 Ku-band pulses (I and Q) and N_Cycle*14 C-band pulses (I

and Q), N_Cycle being the number of cycles in a CAL1 sequence. The first NLRM-Ku Ku-band pulses as well as

the first NLRM-C C-band pulses must be ignored (transition).

A SAR mode sequence contains N_Cycle*64*4 Ku-band pulses (I and Q) and N_Cycle*2*4 C-band pulses

(I and Q). The first NSAR-Ku Ku-band pulses as well as the first NSAR-C C-band pulses must be ignored

(transition).

Whatever the mode is (LRM or SAR):

• For each of the retained Ku-band pulses (I and Q) of the input sequence, a 128*N-points 0-padding FFT is performed and the I2+Q2 spectrum is derived. The average Ku-band 128*N-points I2+Q2 spectrum is then computed.

• The same process is applied to the retained C-band pulses (I and Q) of the input sequence.

In SAR mode, the oversampled complex PTR spectrums are also provided for the Ku pulses of each

retained full burst.

The mode information will be associated to the outputs.

2.4.4 Comments

The Fast Fourier Transforms used in this algorithm shall be performed with zero-padding capability and

shall generate centred complex spectrums considering that the zero-frequency sample is located at

Ind_0_Freq for the standard spectrum and Ind_0_Freq*N_Over for the oversampled spectrum.

The Fast Fourier Transforms have to be normalised dividing by the number of samples (128 for strandard

spectra and 128*N_Over for oversampled spectra).

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2.5 ALT_CAL_PTR_02 – To correct the PTR

2.5.1 Heritage


2.5.2 Function

To correct the Point Target Response (PTR) for the effects of the GPRW.


2.5.3.1 Input data

• PTR and GPRW spectrums :

Samples of the PTR spectrum (128*N I2+Q2 values) Samples of the GPRW spectrum (128*N I2+Q2 values)


Spectrum oversampling factor (N)

2.5.3.2 Output data

• Samples of the PTR corrected for the GPRW effects (128*N I2+Q2 values)


Samples of the PTR (power) are corrected for the GPRW effects by dividing all of them by the value of the

GPRW at the same frequency. When the value of the GPRW equals 0, then the value of the corrected PTR

is set to 0.

The GPRW used to correct the PTR is the closer before the time-tag of the PTR measurement, and such as

the time difference between both measurements is smaller or equal to a threshold.

If no such GPRW measurement is found, then the correction of the PTR is performed from the GPRW from

the CAL2 LTM calibration file, the closer before the time-tag of the PTR measurement, and such as the

time difference between both measurements is smaller or equal to a threshold. This GPRW is

oversampled by linear interpolation to be consistent with the input PTR sampling.

If no such GPRW measurement is found, then the correction of the PTR is performed from a reference

GPRW (instrumental characterization data)

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2.6 ALT_CAL_PTR_03 – To compute the total power of the PTR

2.6.1 Heritage


2.6.2 Function

To compute and check the total power enclosed in the PTR.


2.6.3.1 Input data

• PTR spectrum:

Samples of the PTR spectrum (128*N I2+Q2 values)

• Altimeter instrumental characterization data (DAAD) :

FFT step in frequency (Hz) Index of the 0-frequency sample (/) Reference PTR total power (prelaunch PTR calibration)

Half width of the analysis window for total power computation (f)


Spectrum oversampling factor (N) Threshold percentage on the PTR power estimation

2.6.3.2 Output data

• Total power of the PTR and associated validity flag


The total power enclosed in the PTR spectrum is obtained by summing the value of the samples of the

point target response:

=j

jXP

where Xj is the sample of the PTR and where j represent the indexes of samples whose frequency belongs

to [-f ,f ].

This parameter has to be compared with the total power computed from the reference PTR. One flag for

the total power of the PTR is output.

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2.7 ALT_CAL_PTR_04 – To compute the general features and the features of

the main lobe of the PTR

2.7.1 Heritage


2.7.2 Function

To compute and check the main characteristics of the main lobe of the PTR.


2.7.3.1 Input data

• PTR spectrum :


• Total power of the PTR


Bandwidth of the signal Pulse duration Reference width of the main lobe (prelaunch PTR calibration) Reference difference of travel (prelaunch PTR calibration) FFT step in frequency (Hz) Index of the 0-frequency sample (/)


Spectrum oversampling factor (N) Order of the polynomial used to fit the main lobe Number of points used for the polynomial regression Thresholds and bounds

• Universal constants (SAAD):

Light velocity

2.7.3.2 Output data

• Maximum value of the PTR

• Frequency of the maximum value of the PTR and corresponding distance

• Frequency of the median point of the PTR in energy and associated distance (difference of travel between the Tx/Rx lines)

• Width of the main lobe of the PTR at -3 dB

• Associated validity flags

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The general features and the features of the main lobe of the PTR to be determined are:

• The position (frequency, distance) of the maximum and its value • The half power width of the main lobe • The difference of travel between the transmission and the reference lines (and the associated

frequency)

Position of the maximum value of the main lobe

The precise position of the maximum value of the main lobe is derived according to the following

procedure:

• Search of the sample around the maximum value of the PTR • Selection of N samples around the maximum value (N/2 samples on the left, N/2 samples on the right,

N<7) • Computation of the coefficients of a kth order polynomial that fits these (N+1) samples ( k <=6 ) • Computation of the derivative function of this polynomial • Search of the position of the roots of this derivative function

Once the precise position of the maximum of the main lobe is obtained, the value of this maximum is

recomputed by evaluating the kth order polynomial at the position of the maximum of the main lobe.

Half power width of the main lobe

The half power width is given by the following procedure:

• Computation of the power which is half of the maximum value • Search for the samples around this value (2 on each side of the main lobe) • Computation of the indexes associated with these values by linear interpolation • Conversion of these indexes into frequency • Computation of the difference between the 2 frequencies

Max_Val_PTR

Max_Val_PTR/2

k th order polynomial

Ind _Max_Val_PTR ………… Ind _Max_Val_PTR-1

Ind _Max_Val_PTR+1 ……….. Freq _Max_Val_PTR

Linear regression

Linear regression Width_Main_Lobe

Left_ Freq

Right_ Freq

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Difference of travel between transmission and reference lines

The difference of travel between transmission and reference lines is computed by searching for the index

of the sample that divides the energy of the spectrum by a factor of 2, and then by converting this index

into frequency and distance.

Verification

Parameters to be verified are the width of the main lobe and the difference of travel between the

transmission and the reference lines.

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2.8 ALT_CAL_PTR_05 – To compute the features of the secondary lobes of the

PTR

2.8.1 Heritage


2.8.2 Function

To compute the positions and the values of the maxima of the secondary lobes.


2.8.3.1 Input data

• PTR spectrum:


• Maximum value of the PTR

• Frequency associated with the maximum of the PTR




Spectrum oversampling factor (N) Order of the polynomial used to fit the lobes Number of points used for the polynomial regression Constant of proportionality between the maximum value of the PTR and the limit value allowed for

the secondary lobes Number of secondary lobes (Nb_Sec_Lobe) Number of samples on the right and on the left of the expected position of the secondary lobes

used to determine the maximum of these lobes

2.8.3.2 Output data

• Powers associated with the maxima of the secondary lobes of the PTR

• Frequency of the maxima of the secondary lobes of the PTR

• Flags for the secondary lobes of the PTR

• Likelihood flag for the secondary lobes

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The positions of the maximum of the secondary lobes are determined taking into account that the

distance in frequency between two consecutive lobes is close to the FFT step of the instrument.

Nb_Sec_Lobe secondary lobes have to be considered i.e. Nb_Sec_Lobe/2 lobes for each side of the main

lobe. Knowing the theoretical positions of the secondary lobes, the maximum value that has been

measured is searched in a given window of frequencies. Then, like for the determination of the maximum

of the main lobe, an interpolation is performed around the maximum values of each secondary lobes.

It is also verified that the powers associated to the maximum of the secondary lobes do not exceed a

threshold value of the power of the main lobe.

A likelihood flag associated with the secondary lobes is determined.

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2.9 ALT_CAL_PTR_06 - To compute phase calibration (CAL 1) corrections (SAR

mode)

2.9.1 Heritage

Cryosat-1

2.9.2 Function

To compute phase correction to correct each complex echo of a burst from phase variations within a burst

using instrumental calibration corrections (CAL 1).


2.9.3.1 Input data

• Number of retained full CAL1 bursts

• PTR spectrum:

• Series of oversampled complex PTR (Ku) for each CAL1 burst

2.9.3.2 Output data

• Phase corrections (averaged over the number of bursts)


To perform Doppler beam forming in the azimuth direction, the correlation between the echoes in the

burst is needed. This correlation is ensured thanks to the high PRF value. However, phase variations from

pulse to pulse of the emitted burst, if are not corrected for, prevent from having this correlation.

The phase calibration correction consists in a burst of phases derived from the phases of the PTR peak

values. The phase corrections stand for the opposite of the phase deviations with respect to the phase of

the first pulse of the CAL1 burst.

This algorithm provides an averaging of this phase vector over the number of retained bursts of the CAL1

sequence.

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2.10 ALT_CAL_PTR_07 - To compute power calibration (CAL 1) corrections (SAR

mode)

2.10.1 Heritage

Cryosat-1.

2.10.2 Function

To compute power correction to correct each complex echo of a burst from power variations within a

burst using instrumental calibration corrections (CAL 1).


2.10.3.1 Input data

• Number of retained full CAL1 bursts

• For each CAL1 burst:

• Series of oversampled complex PTR (Ku)

2.10.3.2 Output data

• Burst of power corrections


The power calibration correction consists in a series of powers derived from the 64 PTR total powers of

the pulses occurring in a CAL1 burst. The power corrections vector equal the mean total power (over this

CAL1 burst) divided by each of the 64 total powers.

This algorithm provides an averaging of this power vector over the number of retained bursts of the CAL1

sequence.

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2.11 ALT_CAL_PTR_08 - To compute the AGC correction table (automatic CAL1,

SAR)

2.11.1 Heritage

/

2.11.2 Function

To compute the 62 values of the AGC correction table (AGC real value vs. AGC expected value) for the Ku

and C bands.


2.11.3.1 Input data

• Number of AGC couples (N)

• Table of AGC combinations for the autocal. sequence (Ku band)

• Table of AGC combinations for the autocal. sequence (C band)

• Flag for inverse/forward of the switch (0 or 1)

• Characterisation data

Table of AGC combinations for the tracking sequence

• Number of cycles

• For each couple of gains of the CAL1 SAR sequence:

Complex Ku-band pulses Complex C-band pulses

• Configuration data:

Spectrum oversampling factor (N) Nb of Ku-band pulses to reject at the beginning of the autocal seq. (NSAR-Ku) Nb of C-band pulses to reject at the beginning of the autocal seq. (NSAR-C)




• AGC correction table (Ku-band ref. et corrected values)

• AGC correction table (C-band ref. et corrected values)

• Ku/C switch value (Ku-band)

• Ku/C switch value (C-band)

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The general purpose of the method consists in obtaining a relative calibration of each of the AGC steps

rather than having an absolute measurement of the steps.

It is thus necessary to refer to a reference measure sequence, defined by a couple of commands

ATT1ref/ATT2ref. This choice of the couple is arbitrary and leads to few consequence on the retrieval

accuracy. The reference measure is the first TM of the Autocal sequence.

The principle consist in calibrating the 31 steps of AGC, the other being set, then to permute in order to

calibrate the other configuration. Note that the C/Ku switch calibration is not necessary: for the calibration

sequence, the C/KU switch is kept in an unique position, inverse, in order to calibrate the high power steps

without saturating the receiver.

The full calibration is obtained in 4 sequences, with a doubled state each time, where only the opposite

value of AGC changes. The validity of the method is based on linearity and independence of the AGC.

Note that the C/Ku switch does not need to be calibrated, it can nonetheless be obtained as a by-product

of this method adding a few measurements inverting the C/Ku switch state.

Calibration sequence

The reference sequence equation is described as:

a1[i0] + a2[j0] + b[0] + c0 + α*w[0] = y[0]

where:

a1[i0]: gain of first attenuator for command i0 a2[j0]: gain of second attenuator for command j0 b[0]: noise c0: absolute unknown gain α: Ku/C switch value w[0]: binary flag for inverse/forward position of the switch (0 or 1) at reference (0th measure in the

sequence) y[0]: reference measure

The measure “y” shall be understood as the value corresponding to the maximum of the square module

of the PTR (converted in dB) and is computed as follow.

A measurement corresponding to an AGC couple of a CAL1 SAR sequence contains N_Cycle*64*4 Ku-band

I/Q pulses and N_Cycle*2*4 C-band I/Q pulses. The first NSAR-Ku Ku-band pulses and the first NSAR-C C-band

pulses must be ignored (transition) from the set of the Ku-band pulses and C-band pulses, respectively.

• For each of the retained Ku-band pulses (I and Q) of the input sequence, a 128*N-points 0-padding FFT is performed and the I2+Q2 spectrum is derived. The average Ku-band 128*N-points I2+Q2 spectrum is then computed.

• The same process is applied to the retained C-band pulses (I and Q) of the input sequence.

In SAR mode, the oversampled complex PTR spectrums are also provided for the Ku pulses of each

retained full burst.

The mode information will be associated to the outputs.

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For each of the retained Ku-band pulses (I and Q) corresponding to an AGC couple (Att1/Att2 values), a

128*N-points 0-padding FFT is performed and the I2+Q2 spectrum is derived. The average Ku-band

128*N-points I2+Q2 spectrum is then computed and its maximum computed and converted in dB.

Similarly, the average C-band I2+Q2 spectrum is obtained and its maximum derived in dB.

Then the N measures done during the calibration sequence lead to the following system:

a1[in] + a2[jn] + b[n] + c0 + α*w[n] = y[n]

where:

a1[k] is the gain of first attenuator for the k step (0 ≤ k ≤ 31) a2[k] the gain of second attenuator for the k step (0 ≤ k ≤ 31) c0 is absolute unknown gain α: Ku/C switch value w[n]: binary flag for inverse/forward position of the switch (0 or 1) at nth measure in the sequence b[n] is measure noise y[n] is nth measure of the calibration sequence in is integer value (comprised between 0 et 31) corresponding to the command applied to the first

amplifier for the nth measure. jn is integer value (comprised between 0 et 31) corresponding to the command applied to the

second amplifier for the nth measure.

Notes:

1. As previously explained it is not expected to obtain directly the gain values but deriving them for

relative measurements from a reference.

2. The calibration sequence is stored in RDB, it will be available in the SCCDB as a copy, it is also available

through the direct reading of the AGC (Att1/2) command in the TM sequence of the CAL autocal.

The reference value is thus subtracted from each of the N measures. The nth corrected measure is then

described by the following equation:

x1[in] – x2[jn] + α*(w[n] – w[0]) + v[n] = z[n]

where:

x1[k] = a1[k] - a1[i0]: relative gain of attenuator 1 for command k (0 ≤ k ≤ 31, x1[i0]=0) x2[k] = a2[k] – a2[j0]: relative gain of attenuator 2 for command k (0 ≤ k ≤ 31, x2[j0]=0) z[n] = y[n] - y[0]: measure n (after subtraction of reference measure) v[n] : noise for measure n

There are then 63 values to estimate:

the 31 relative gains of the 1st attenuator (x1[k], 0 ≤ k ≤ 31, k ≠ i0) the 31 relative gains of the 2nd attenuator (x2[k], 0 ≤ k ≤ 31, k ≠ j0) α, switch attenuation

Switching to matrix formalism then:

Hε + V = Z

where:

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ε is a column vector with 63 parameters to estimate (arranged by 31 attenuator #1 values first, then 31 attenuator #2 values and α at the end)

H is a deterministic matrix with N lines and 63 columns. This matrix is built as follow:

first H0 with N lines and 64 columns, where the nth line is set with value 1 at columns in+1 and jn+33, the rest being 0,

H is the obtained deleting columns i0+1 and j0+33 of matrix H0,

then a last column vector is added at right position containing the N values (w[n] - w[0])

V is a random column modelling the received noise. In practical, the SNR is guaranteed to have sufficient values so it can be approximated that every measure has the same noise without perturbing the inversion. The correlation matrix of noise is then Γv = σb

2 Id. For the next step, of the processing the noise influence will be neglected leading to a simpler algorithm where there is non need for noise estimation at each attenuator step.

Z is the column vector containing the N corrected measures relatively to the reference measure.

From a practical point of view, the H matrix building is derived from the Cal1_AGC_sequence matrix, which

is either preferably directly derived from the Att1 / Att2 positions and switch position reading in the TM

sequence, or a reading from the SCCDB (as a copy of the sequence in RDB).

The reference attenuation for reference indexes i0 and j0, are also stored in the SCCDB and correspond

to the FIRST values in the table Cal1_AGC_sequence, they are also directly reachable in the TM as the first

Att1/Att2 couple of the first TM in the autocal TM sequence (note that the “ideal” attenuation and the

index covers the same values a1[i]=a2[i]=i, 0 ≤ i ≤ 31).

Estimation of relative gains and switch isolation

The next steps address a least square solving in order to estimate the relative attenuation ε from the

observables Z (there is no unicity of solution). The 31 first values of the estimation ε_cap of ε are the

estimates of the relative gains of the first attenuator (x1[k], 0 ≤ k ≤ 31, k ≠ i0), the 31 next for the second

attenuator (x2[k], 0 ≤ k ≤ 31, k ≠ j0). The last value of ε_cap contains the estimation of the switch isolation

α.

Tracking law reconstitution

From ε_cap the vector x_cap of 64 cells in size is built by inserting a zero at lines i0+1 and j0+33, and

cancelling the last value of the ε_cap vector.

The distribution law of the gains used in tracking is then built. If g[n] is the nth combination of the

distribution law, then the matrix formulation is:

g_cap = G * x_cap

where G is a 63 lines matrix (corresponding to dynamic 0 à 62 dB), et 64 columns (corresponding to two

times the 32 steps of attenuators). The G matrix building is identical to H0, but using the distribution law

of tracking instead of calibration law.

Note that g_cap is a biased estimator of the distribution law (due to relative gains processing).

From a practical point of view, the i0 and j0 values are directly obtained from the ATT1 and ATT2 values

of the first sequence in the TM sequence or the first values of Cal1_AGC_sequence in SCCDB. (note that

as the “ideal” attenuation and the index covers the same values a1[i]=a2[i]=i, 0 ≤ i ≤ 31).

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The G matrix building is derived from the AGC_ref_table matrix, which is obtained from the SCCDB (as a

copy of the sequence in RDB).

AGC correction table

The “attenuation” table is then obtained subtracting from g_cap the value of the first cell (then always

starting at 0). The Attenuation table contains the estimated attenuation steps ordered from 0 to 62 dB.

2.11.4 Comments

This algorithm addresses the relative calibration of the gains. Therefore the PTR processing does not

consider:

• An oversampling of the PTR (focusing on the relative variations of the maximum)

• The correction of CAL2 filter (same CAL2 parameters hold for the all the PTR processed during the autocalibration sequence)

The routines proposed as a least square solution of Eq. 4 rely on the assumption that the number of lines

of the matrix H (NB_AGC_Couples) is greater than the number of columns (62).

The Fast Fourier Transforms used in this algorithm shall generate centred complex spectrums considering

that the zero-frequency sample is located at Ind_0_Freq for the standard spectrum and

Ind_0_Freq*N_Over_AutoCal for the oversampled spectrum.

The Fast Fourier Transforms have to be normalised dividing by the number of samples (128 for strandard

spectra and 128*N_Over for oversampled spectra)

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2.12 ALT_CON_TIM_01 - To convert the on-board time counters into GPS times

2.12.1 Heritage

Jason-1 (Poseidon-2), Jason-2 (Poseidon-3).

2.12.2 Function

To convert the on-board time counters into GPS time.


2.12.3.1 Input data

• Datation : Coarse time (counter), Fine time (counter), SRAL fine datation (counter)

• Burst number (relevant in SAR mode)

• Burst repetition frequency (relevant in SAR mode)


• Raw GPS time


The on-board synchronization of OBT and GPS time is such as the difference between these two

parameters does not exceed 1 s. The OBT time may thus be directly considered as the GPS time without

additional processing.

A simple addition of each item is performed.

In SAR mode, the four bursts of a tracking cycle contain the same datation. Time for each burst is then

deduced from brurst repetition frequency.

For NAVATT ISP, only coarse time and fine time are relevant to determine packet time.

2.12.4 Comments

In LRM mode, ISP_Burst_Number and BRF are not pertinent: ISP_Burst_Number is then arbitrarily set to

1 to annihilate its contribution in equation (1).

For NAVATT ISP, ISP_SRAL_Fine_Datation is not pertinent and is then arbitrarily set to 0 to annihilate its

contribution in equation (1).

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2.13 ALT_CON_TIM_02 - To reference the time-tags to the measurement on the

overflown surface

2.13.1 Heritage


2.13.2 Function

To reference the GPS time-tag of measurements to the moment of the physical measurement of the

altimeter at the overflown surface level.


2.13.3.1 Input data

• Mode identifier

• Datation :

GPS time derived from the on-board time counter

• Information allowing the estimation of the distance between the altimeter and the overflown surface:

Applied altitude command


Nominal pulse repetition frequency in LRM mode Nominal pulse repetition frequency within the burst in SAR mode Time shift accounting for internal delays to reference the midlle of the tracking cycle in LRM mode Time shift accounting for internal delays to reference the midlle of the burst in SAR mode Ambiguity order in LRM mode Number of pulse repetition intervalls between the transmissions of the first (respectively last) C

pulse and the first (respectively last) Ku pulse of a burst in SAR mode


Time biases (LRM and SAR modes)


• Corrected GPS time


The input raw GPS times T derived from on-board time counters are corrected, by:

• Referencing the time-tag to the centre of the measurement :

For LRM mode, the time-tag is referenced to the centre of the tracking cycle, by adding to T

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XPRF

1

2

1N+

−=

where:

o N is the total number of pulses per waveform o PRF is the nominal pulse repetition frequency o X is the time shift to reference the midlle of the tracking cycle

For SAR mode, the time-tag is referenced to the centre of the burst, by adding to T:

YPRF

1

2

1ML

burst

+

−+=

where:

o L is the number of pulse repetition intervalls between the transmissions of the first (respectively last) C pulse and the first (respectively last) Ku pulse of a burst

o M is the number of Ku-band pulses per burst o PRFburst is the nominal pulse repetition frequency within the burst in SAR mode o Y is the time shift to reference the midlle of the burst

• Adding a possible datation bias for LRM and for SAR modes (processing parameters)

• Adding (because the datation event corresponds to the emission of a pulse) the propagation delay of a pulse from the altimeter towards the overflown surface H0

• Adding for the LRM mode an estimation derived from the ambiguity order (Amb):

PRF

AmbD −=

2.13.4 Accuracy

This processing is specific to measurements for which a very accurate datation is expected (precision

better than some microseconds), i.e. to tracking measurements (LRM mode and SAR mode). It does not

concern and is not applied to the other modes (e.g. internal calibrations, acquisition …).

The propagation delay of a pulse from the overflown surface towards the altimeter is derived from the

ambiguity order and the applied command H0, ignoring with respect to the exact computation, the USO

drift, the fine trigger delay, a possible offset between the reference sample for tracking and the centre of

the analysis window as well as the assumption that H0 is referenced to the center of the tracking cycle

while it corresponds to the first pulse of the first burst. The maximum error concerning these last two

points will not exceed some samples or tens of samples and will thus be smaller than some tens or

hundreds of nanoseconds. Regarding the USO drift, the error should remain smaller than some centimers,

equivalent also to some nanoseconds. The approximation is thus precise enough with respect to a time

resolution of 1 microsecond.

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2.14 ALT_CON_TIM_03 - To compute the time-tag of C band measurements in

SAR mode over a tracking cycle

2.14.1 Heritage

None

2.14.2 Function

To reference the C-band measurements perfomed in SAR mode to a tracking cycle, i.e. to the centre of

the four bursts representing the tracking cycle (moment of the physical measurement of the altimeter at

the overflown surface level).

This time tag is also applicable to the pseudo-LRM mode.


2.14.3.1 Input data

• Datation :

Corrected GPS time of the 4th burst of a tracking cycle


Nominal burst repetition frequency Number of bursts per tracking cycle


• Corrected GPS time corresponding to the centre of the tracking cycle


The input corrected GPS time t, corresponding to the time-tag of the fourth burst of a tracking cycle, is

referenced to the centre of the tracking cycle by adding to t:

BRF

1

2

1N

−−=

where: N is the number of bursts per tracking cycle

BRF is the nominal burst repetition frequency

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2.15 ALT_COR_RAN_01 – To compute the internal path correction and the

corrected tracker ranges

2.15.1 Heritage


2.15.2 Function

To compute the internal path correction on the altimeter range, accounting in particular for the difference

of travel between the transmission and the reference lines within the altimeter (LTM calibration

parameter), and to correct the tracker ranges.


2.15.3.1 Input data

• Datation:

Altimeter time-tag

• Tracker range

• Time-stamped CAL1 internal calibration parameters (DAAD):

Difference of travel between the transmission and the reference lines within the altimeter

• Altimeter instrumental characterization data :

Distance between the duplexer and the antenna reference point (2-ways path)


• Internal path correction on the altimeter range

• Corrected tracker range


Principle

As represented in the figure below, the distance d measured by the altimeter is given by:

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AG-FG+CF+2.HI+2.EH+2.DE+2.CD+BC+AB

AG)FGCFDCED(HEIHHIEH)DECDBCAB(d

=

−+++++++++++=(1)

where points D and H are respectively outside and inside the antenna.

The altimeter range, i.e. the distance HI between the surface and the reference point of the antenna is

thus:

( )AG+FG-CF-2.EH-2.DE-2.CD-BC-ABd2

1=HI − (2)

The difference of travel dcal (distance) between the transmission and the reference lines provided by the

internal calibration corresponds to:

( )AGFGBFAB2

1dcal −++= (3)

Moreover, the following distance difference may be characterized on-ground before launch:

BFCFBCdr −+= (4)

The distances CE and EH may also be characterized before launch and thus a single parameter is requested

from the altimeter features set to compute the internal correction path. This parameter represents the

distance between the duplexer and the antenna reference point, and is given by:

( )2

EHCE*2dd r

antennaduplexer

++=− (5)

where the numerator represents the parameter which is actually characterized (“Distance between the

duplexer and the antenna reference point / 2-ways path”).

Combining (2) with (3) and (5), the altimeter range is given by:

(6)

In this equation, d/2 represents the raw value of the altimeter range and the internal path correction to

be added to this value is thus:

( )antennaduplexercal dd=h −+− (7)

Computation of the internal path correction

SurfaceA

B

C D E

F

G

H

I

SurfaceA

B

C D E

F

G

H

I

( )antennaduplexercal dd2

d=HI −+−

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For each band, the processing is the following:

• Selection of the dcal calibration parameter (averaging of calibration points over a predefined window characterized by a duration before and a duration after the processed measurement).

• Computation of the correction h according to (7)

The Ku and C band tracker ranges, already corrected for the USO frequency drift, are corrected by

adding the corresponding internal path correction (internal calibration correction)

• Computation of the corrected tracker range by adding h to the input tracker range

2.15.4 Comments

The distance between the antenna and the centre of gravity of the satellite will be taken into account in

the Level 2 processing where platform data (NRT, STC and NTC estimates) will be available.

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2.16 ALT_COR_RAN_02 – To compute the Doppler correction and the corrected

tracker ranges (LRM mode)

2.16.1 Heritage


2.16.2 Function

To compute the Doppler corrections on the altimeter range, and to correct the tracker ranges.


2.16.3.1 Input data

• Orbital altitude rate

• Tracker range

• Altimeter instrumental characterization data :

Emitted frequency Pulse duration Emitted bandwidth Sign of the slope of the transmitted chirp


• Doppler correction

• Corrected tracker range


For each band, the Doppler correction to be added to the altimeter range is computed by:

'h.B

T.f.hDoppler −=

where:

h' is the altitude rate f is the emitted frequency T is the pulse duration B is the emitted bandwidth

= 1 is the sign of the slope of the transmitted chirp

The corrected tracker range is obtained by adding the Doppler correction to the input tracker range.

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2.16.4 Accuracy

Assuming instrumental features such as:

f = 13.575 GHz (Ku) and 5.41 GHz (C) B = 320 MHz (Ku) and 290 MHz (C)

T = 44.8 s

• An error of 0.1 mm on the Ku band Doppler correction will be reached for an orbital altitude rate error exceeding 5 cm/s for Ku band.

• An error of 0.1 mm on the C band Doppler correction will be reached for an orbital altitude rate error exceeding 12 cm/s.

2.16.5 Comments

• In order to ensure the continuity of the Doppler correction whatever the surface type is, the altitude rate involved in its expression originates from the orbit, and is not the tracker estimate or an estimate derived from the altimeter range retracked estimates.

• The part of the altitude rate due to the variation of the sea surface height (geoid or mean sea surface with respect to ellipsoid) is not accounted for in the Level 1b Doppler correction. It will be taken into account in the Level 2 processing

2.16.6 References

Chelton D.B., Walsh E.J., and MacArthur J.L., 1989, Pulse compression and sea-level tracking in satellite

altimetry, J. Atmos. Oceanic Technol., 6, 407-438.

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2.17 ALT_COR_RAN_04 - To compute and apply Doppler correction (SAR mode)

2.17.1 Heritage

Cryosat-1.

2.17.2 Function

To compute and apply the Doppler correction on the Doppler beams (frequency domain) previously

computed for each burst.


2.17.3.1 Input data

• Orbit:

Satellite velocity

• For each burst:

Doppler beams Doppler beam directions angles

• Altimeter instrumental characterization data (Ku-band):

Emitted frequency Pulse duration Emitted bandwidth Sign of the slope of the chirp


Light velocity


• The Doppler beams for each burst of pulse-limited time domain echoes corrected for Ku-band Doppler corrections

• Doppler corrections


For each burst, the Doppler shift of beam number n is computed by:

)n(cosVB

T.f.)n(rDoppler −=

where:

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n is the beam number V is the satellite velocity

is the Doppler beam direction relative to satellite velocity vector f is the emitted frequency T is the pulse duration B is the emitted bandwidth

= 1 is the sign of the slope of the transmitted chirp

The Doppler shift to be applied to the Doppler beams is opposite to the Doppler correction. This Doppler

correction is then applied by using the FFT function theorem that can be expressed by the following

equation:

The needed frequency translation (using the fact that the round-trip time is proportional to frequency

when performing the pulse compression operation) is:

rc

K2f =

r being the range correction, in this case it is the Doppler range correction rDoppler. K is the chirp slope

and c the light velocity. The chirp slope K is given by:

K = B/T

B being the emitted bandwidth and T the pulse duration.

The phase compensation term can then be written as:

]t)n(rc

K2j2exp[)t,n( Doppler−=

n corresponds to the beam number and t the time or abscissa of the time domain echoes.

The matrix corresponding to the burst of beams in the time domain is simply multiplied by this phase

compensation matrix.

2.17.4 Comments

• In order to ensure the continuity of the Doppler correction whatever the surface type is, the spacecraft velocity involved in its expression originates from the orbit, and is not the tracker estimate.

• The part of the altitude rate due to the variation of the sea surface height (geoid or mean sea surface with respect to ellipsoid) is not accounted for in the level 1b Doppler correction.

) 2 exp( ). ( )) ( ( fa j G TF a x G TF − = −

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2.18 ALT_COR_RAN_05 - To compute the slant range correction (SAR mode)

2.18.1 Heritage

Cryosat-1.

2.18.2 Function

To compute the slant rang correction for each Doppler beam within a burst and to separate the coarse

and fine contributions.


2.18.3.1 Input data

• Range at reference surface locations

• Position at reference surface locations

• Satellite position at each burst

• For each burst:

Number of beams Associated indices of reference surface positions

• Altimeter instrumental characterization data (Ku-band):

FFT step in time


Light velocity


• For each beam of each burst:

• Coarse slant range correction at the range window resolution (for application after range compression)

• Fine slant range correction defined as the remainder of the true value and the range bin integer from the coarse correction (for application to time domain sample waveforms)


If we consider a surface point in the along track position, this point should be located at the nadir

corresponding sample (tracker bin). But this point if it is far away from the nadir will have a round-trip

distance that corresponds to greater sample numbers. It is then necessary to correct from this effect to

realign the different positions.

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Figure 2-1 Determination of slant range correction

The range migration can be written (Raney, 1998):

(1)

R is related to the Earth roundness and is expressed as:

hn is the range at the reference surface location n.

RE being the Earth radius. The range migration can also be expressed versus the Doppler frequency:

)]n([cos2

hf

V8

h)n(r 2nR2

D2n

2R

Slant

=

• n is, for beam number n, the Doppler beam direction relative to satellite velocity vector.

• Without approximation, range migration can also be expressed as follow:

E

nER

R

hR +=

rn n

Orbit V

rn hn

x0-xn

n

n R

n

n R n n n

h

x x

h

x x h h r r

2

) ( 1

) ( 1

2 0

2

2 0

n −

−

− + = − =

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n0

n0

n0

n222

n

zzz

yyy

xxx

With:

,hzyxr

−=

−=

−=

−++=

• (x0,y0,z0) being the coordinates of the satellite position at the burst measurement and (xn,yn,zn) the coordinates of the reference surface location.

2.18.4 References

Raney, R. K, The Delay/Doppler Radar Altimeter, IEEE Trans. On Geosc. And Remote Sensing, Vol. 36, No.

5, September, 1998.

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2.19 ALT_COR_WAV_01 – To correct the waveforms for the GPRW (LRM mode)

2.19.1 Heritage


2.19.2 Function

To correct the waveforms (LRM mode) for the effect of the GPRW (LTM calibration parameters).


2.19.3.1 Input data

• Datation:

Altimeter time-tag

• Waveform (128 samples)


Normalized GPRW


• Corrected waveform (128 samples)


Let {Vi}i=0,N be the input waveform and {fi} i=0,N be the corresponding normalized anti-alias filter (GPRW).

Assuming that the effect of the positionning of the waveform in the analysis window by the fine trigger

delay is negligible with regard to the 20-Hz global effect of the anti-alias filter on the waveform, the

corrected waveform {Vci}i=0,N may be retrieved by:

i

ici

f

VV =

The GPRW to be used is got from averaging of calibration points over a predefined window characterized

by a duration before and a duration after the processed measurement.

This correction will be applied to Ku- and C-band data.

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2.20 ALT_COR_WAV_02 - To apply phase calibration (CAL 1) corrections (SAR

mode)

2.20.1 Heritage

Cryosat-1

2.20.2 Function

To correct each complex echo of a burst from phase variations within a burst using instrumental

calibration corrections (CAL 1).


2.20.3.1 Input data

• Internal calibration parameters (CAL1): phase corrections

• Burst of waveforms in the time domain


• Corrected burst of complex time domain echoes


To perform Doppler beam forming in the azimuth direction, the correlation between the echoes in the

burst is needed. This correlation is ensured thanks to the high PRF value. However, phase variations from

pulse to pulse of the emitted burst, if are not corrected for, prevent from having this correlation. To

correct from this phase variations, a burst of CAL 1 echoes is used.

This correction is applied in the time domain. The phase correction consists in a burst of phase vectors.

For each pulse of the burst each sample of the time domain echoes is simply multiplied by a complex

whose amplitude is one and whose phase is equal to the CAL1 phase (in the time domain).

F(tn,np) is the burst of echoes in the time domain. Np is the pulse number in the burst and tn is the pulse

time sample. G(tn,np) is the phase correction. The corrected burst Fc(tn,np) is expressed as:

Fc(tn,np) = F(tn,np).e(iG(tn,np))

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2.21 ALT_COR_WAV_03 - To apply power calibration (CAL 1) corrections (SAR

mode)

2.21.1 Heritage

Cryosat-1

2.21.2 Function

To correct each complex echo of a burst from power variations within a burst using instrumental

calibration corrections (CAL 1).


2.21.3.1 Input data

• Internal calibration parameters (CAL1): power corrections

• Burst of waveforms in the time domain


• Corrected burst of complex time domain echoes


This correction is applied in the time domain. It consists in simply multiplying each pulse (all the samples)

of the burst by the corresponding power correction.

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2.22 ALT_COR_WAV_04 – To correct the waveforms for GPRW (SAR mode)

2.22.1 Heritage

Cryosat-1

2.22.2 Function

To correct complex waveforms from the frequency dependent gain profile provided by instrumental

calibration corrections.


2.22.3.1 Input data

• Datation:

Altimeter time-tag

• Complex echoes of a burst

• Time-stamped LTM calibration parameters (DAAD):

Normalized GPRW




• Gain profile corrected burst of complex time domain echoes


The gain profile is frequency dependent. The waveforms have then to be corrected in the frequency

domain. For that an FFT operation is applied to each of the burst pulses. The result is a burst of complex

frequency domain echoes. A FFTshift operation is applied here on these complex frequency domain

echoes to shift zero-frequency component to center of spectrum: this allows gain profile and waveform

to be consistent.

Let {Vi}i=0,N be the complex waveforms in the frequency domain and {fi} i=0,N be the corresponding

normalized anti-alias filter (GPRW). Assuming that the effect of the positionning of the waveform in the

analysis window by the fine trigger delay is negligible with regards to the 20-Hz global effect of the anti-

alias filter on the waveform, the corrected waveform {Vci}i=0,N may be retrieved by:

i

ici

f

VV =

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An inverse FFT is then applied to the corrected burst to get a burst of complex pulses in the time domain.

• The GPRW to be used is got from averaging of calibration points over a predefined window characterized by a duration before and a duration after the processed measurement.

• This correction will be applied to Ku-band data.

• It will also be applied to C-band data in case of generation of L1a products

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2.23 ALT_COR_WAV_05 - To correct waveforms from AGC (SAR mode)

2.23.1 Heritage

Cryosat-1

2.23.2 Function

To correct complex waveforms from the AGC commands.


2.23.3.1 Input data

• Ku-band complex echoes of a burst

• ATT:

ATT applied onboard and corrected from instrumental effects


• Burst of complex waveforms corrected from AGC


A different gain command is applied onboard to each cycle of waveforms (4 bursts of waveforms). In the

SAR mode, the bursts of echoes are processed in azimuth (Doppler processing). At each surface location,

the resulting waveform consists in a stack of beams that come from different bursts of echoes. As a result,

the waveforms have to be corrected for the ATT, to allow stacking quantities in the same units.

Let {Vi}i=0,N be the complex waveforms in the time domain and ATT the corresponding Attenuation

command applied on-board and corrected from instrumental corrections. The corrected waveform

{Vci}i=0,N may be retrieved by:

10

ATT

ici

10

VV

−=

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2.24 ALT_COR_WAV_06 - To generate the Doppler beams (SAR mode)

2.24.1 Heritage

The heritage of this algorithm relies on the technical characterisation of a Delay/Doppler Radar Altimeter

(Raney, 1998).

2.24.2 Function

To form the Doppler Beams, i.e. to generate a burst of Doppler beams from each burst of pulse-limited

time domain echoes, using a FFT in the along track direction.


2.24.3.1 Input data

• Orbit:

Satellite velocity

• For each burst:

Complex echoes (I,Q) in the time domain Doppler beam direction angles and associated reference surface elevations


Emitted frequency (Ku-band) Pulse repetition frequency (Ku-band, SAR mode)


Surface elevations RMS threshold


Light velocity


• Burst of Doppler beams for the burst of pulse-limited time domain echoes

• Variability surface flag

• Surface variability


To form Doppler beams using a burst of waveforms in the time domain, we simply apply an FFT across the

burst (along track). Before applying the FFT, phase shifts are needed to direct the beams to the

determined surface locations. The operation depends on the nature of the overflown surface.

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In case of low variability, the FFT operation is performed after shifting the phase along the burst (beams

will be directed towards the reference surface samples). The phase shift is computed using the minimum

beam direction angle. The corresponding Doppler frequency shift is given by:

fD = 2Vcos/

V being the platform speed absolute value at this location and the wavelength.

In case of high variability, applying the above process will lead to doppler beam not exactly located at the

same points on the surface (Figure 2-2). The preceding operation is then repeated for each beam so as to

direct it towards the corresponding surface point with a high precision. The variability of the surface is

estimated from the on-board tracker estimates.

Figure 2-2 Influence of surface topography on Doppler beams location

2.24.4 References


5, September, 1998.

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2.25 ALT_COR_WAV_07 - To apply the fine slant range correction (SAR mode)

2.25.1 Heritage

Cryosat-1.

2.25.2 Function

To apply the fine slant range correction in the form of a time domain phase shift to Doppler beam time

domain waveforms.


2.25.3.1 Input data

• For each burst:

Doppler beams corrected from Doppler range Fine slant range correction for each beam


Pulse duration Emitted bandwidth FFT step in time


Light velocity


• Burst of Doppler beams for the burst of pulse-limited time domain echoes corrected for the fine slant range correction.


To correct from this range migration we use the FFT function theorem that can be expressed by the

following equation:



rc

K2f = (2)

) 2 exp( ). ( )) ( ( fa j G TF a x G TF − = −

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r being the range correction, in this case it is the fine slant range Drslant correction. K is the chirp slope

and c the light velocity. The chirp slope K is given by

K = B/T

B being the emitted bandwidth and T the pulse duration.


]t)n(rc

K2j2exp[)t,n( slant_Fine=

n corresponds to the beam number and t the time or abscissa of the time domain echoes.



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2.26 ALT_COR_WAV_09 - To perform range compression (SAR mode)

2.26.1 Heritage

Topex/Poseidon, Jason-1, Jason-2.

2.26.2 Function

To perform a range compression of the waveform, i.e. to convert each Doppler processed burst of pulse-

width time domain echoes to the frequency domain, using an FFT, and generate the power waveforms.


2.26.3.1 Input data

• Burst of corrected Doppler beams in the time domain


• Burst of power beams in the frequency domain (power waveforms)

• Burst of Doppler beams in the frequency domain (complex)


The burst of Doppler beams in the time domain is converted into a burst of beams in the frequency domain

by simply applying a FFT operation in the cross track direction. The power waveforms are then computed.

This operation is the same than the one applied onboard in the case of LRM mode.

In case of génération of L1bs products, bursts of Doppler beams in the frequency domain (complex) are

also computed in the same way.

2.26.4 Comments

This procedure is traditionally applied on-board for pulse-width limited altimeters.

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2.27 ALT_COR_WAV_10 - To apply the coarse slant range and tracker

misalignment corrections (SAR mode)

2.27.1 Heritage

None

2.27.2 Function

For each surface location, the corresponding waveforms have to be aligned before multi-looking by

applying the coarse slant range and tracker misalignment corrections.


2.27.3.1 Input data

• Closest tracker range at reference surface locations

• For each burst:

Tracker range at burst centre Coarse slant range correction Range compressed I2+Q2 waveforms

− Range compressed I&Q waveforms in the frequency domain


FFT step in time


Light velocity


• Burst of power beams aligned for slant range and tracker misalignment in the frequency domain

• Burst of complex beams aligned for slant range and tracker misalignment in the frequency domain


The coarse slant range correction is applied on the range compressed waveforms.

In case of generation of L1bs products, it is also applied to I&Q waveforms (in frequency domain).

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For each burst the different beams will be shifted according to the difference between the tracking range

applied to the burst and the tracking range corresponding to the surface location of the beam.

The tracking range corresponding to the surface location of the beam is determined using the tracker

range of the burst corresponding to the closest location. It is determined in the algorithm that determines

the surface locations.

For each burst, the corresponding tracker range is Ho. For beam number n of that burst, the corresponding

tracking range at the corresponding surface location is Hn.

The aim of this operation is to shift the waveforms so that they appear in the time frame as obtained with

the appropriate Hn tracker command window.

The tracker range misalignment correction corresponds – for each burst - to the shift of the waveforms n

by (Ho-Hn)*2/c/τ in the frequency domain (where c is the light velocity and τ the FFT step in time).

It is added to the coarse slant range correction

In case of generation of L1BS products, bursts of complex beams aligned in the frequency domain are also

computed in the same way.

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2.28 ALT_COR_WAV_11 - To perform the Doppler beams stack multi-looking

(SAR mode)

2.28.1 Heritage

Cryosat-1.

2.28.2 Function

To perform Doppler beam stack multi-look, i.e. to compute stacked sample Doppler beams (I2+Q2

waveforms), i.e. non-coherent summation of all the beams corresponding to each surface location.


2.28.3.1 Input data

• Reference surface locations

• Bursts of power beams in the frequency domain

• Burst of complex beams in the frequency domain

• Corresponding reference surface location and steering angle for each beam

• Variability surface flag

• Index if the burst corresponding to the closest tracker range

• Configuration data:

Min. and max indices for WF noise estimation


• Complex echoes corresponding to the Doppler beams stack

• Stacked sample Doppler beam power echoes

• Number of beams stacked and Doppler beam angles

• Beam behaviour parameters


For each surface location, a search is performed to determine the bursts that contain beams directed to

this location and a threshold on the noise of the waveforms is applied.

The retrieved beams are simply summed and their number is computed as well as the selected Doppler

beam angles.

Before summing, some parameters are computed from the beams:

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• Maximum power of the stack (fitted Gaussian) • Standard deviation of the stack (fitted Gaussian) • Stack skewness and kurtosis (fitted Gaussian)

In case of génération of L1BS products, complex echoes corresponding to the Doppler beams stack are

output.

2.28.4 Comments

Warning: the software will need to optimise the handling of the burst flow.

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2.29 ALT_COR_WAV_12 - To compute the LRM Like Ku and C band power

waveforms from SAR mode pulses

2.29.1 Heritage

None

2.29.2 Function

To compute the LRM-like Ku and C band power waveforms from SAR mode pulses. The on board tracker

is taken into account to align the pulses before power summation.


2.29.3.1 Input data

• Tracking cycle of 4 bursts:

Complex echoes (I,Q) in the time domain Each cycle contains 4 bursts of 1C / 64 Ku / 1C pulses

• For each burst of the cycle :

64 Ku-band pulses (each of them consisting of 128 I and Q complex values) 2 C-band pulses (each of them consisting of 128 I and Q complex values)

• Tracker Range for tracking cycle (the same value is duplicated in the four burst of the cycle)

Tracker Range counter Tracker Range Rate Counter


Emitted bandwidth Pulse repetition frequency within a burst Length of the tracking cycle Number of pulses repetition intervals between the transmission of the first (respectively last) C

pulse and the first (respectively last) Ku pulse of a burst in SAR mode Number of pulses for Ku and C band in a tracking cycle Index of the 0-frequency sample Gains:

"Fine trigger delay" FFT gain in tracking mode (Ku or C)

"Accumulation" FFT gain in tracking mode (Ku or C)

Processing parameters

Gain bias in Ku and C bands


For each cycle

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• One Ku band LRM-Like waveform in the power domain

• One C band LRM-Like waveform in the power domain

• SNR estimation for PLRM Ku band

• SNR estimation for PLRM C band


In a tracking cycle, the tracking range rate from pulse to pulse within a burst is computed using the tracking

range rate counter:

HPR_Pulse_SAR=COR2/Nimp_Pulse_SAR

COR2 is the tracker range rate counter.

Nimp_Pulse_SAR is the number of pulses in a tracking cycle corresponding to continue pulses emission

(case of continue emission of SAR pulses in a tracking cycle as for LRM mode). It is computed using the

PRF in the SAR mode and the length of the tracking cycle:

Nimp_Pulse_SAR = PRF_SAR*Tracking_Cycle_length

Tracker range for the first pulse of each burst

The tracker range command counter available in the ISP is the one computed by the tracker loops from

the previous tracking cycle. It has been applied onboard to the first burst of the tracking cycle.

The tracker range counters corresponding to the four bursts of the tracking cycle are computed using the

following equation:

H(k_burst)=H0 + k_burst*COR2/4

H0 being the tracker range counter, COR2 the tracker range rate (both of them duplicated in the four ISPs

corresponding to the four bursts of the tracking cycle) and k_burst the burst number (from 0 to 3).

In the SAR mode, the waveforms are kept in I&Q and no fft is applied on-board to generate the power

echoes. Consequently, only the coarse range command is applied. For each burst we derive the coarse

range command using the following equation:

H_coarse(k_burst)=round(H(k_burst)/2^8))*2^8

H_fine(k_burst)=H(k_burst) – H_coarse(k_burst)

Tracker range for Ku band SAR mode pulses

The tracker range for each SAR Ku pulses that would have been applied in the case of on-board alignment

of the pulses is given by:

H_Ku_Pulse(k_burst,l_pulse)=H_coarse(k_burst)+H_Fine(k_burst)+(l_pulse+L)*HPR_Pulse_SAR

• K_burst is the number of the burst within the tracking cycle (from 0 to 3) • L_pulse is the number of the Ku pulse within burst k_burst (from 0 to 63)

L is the number of intervals between the first respectively last) C band pulse and the first (respectively

last) Ku pulse

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Tracker range for C band SAR mode pulses

In the SAR mode, each burst contains only two C band pulses one in the beginning and the second in the

end of the burst.

Between the first (respectively last) C band pulse and the first (respectively last) Ku pulse there is L pulses

repetition intervals. The tracker range for both SAR C pulses that would have been applied in the case of

on-board alignment of the pulses is given by:

H_C_Pulse(k_burst,1)=H_corse(k_burst)+H_fine(k_burst)

H_C_Pulse(k_burst,2)=H_corse(k_burst)+H_fine(k_burst)+(64+2*L-1)*HPR_Pulse_SAR

Computation of the distance shift to be applied to SAR mode pulses before building the power echoes

The shift in distance (expressed in time) is simply computed by the difference between the applied tracker

range on-board and the tracker command that would have been applied if an alignment has been

considered.

For each burst, the shift in distance for Ku band pulse l_pulse is :

Shift_distance_Ku(l_pulse)=-H_fine(k_burst)-(l_pulse+L)*HPR_Pulse_SAR

For each burst, the shift in distance for the two C band pulse is :

Shift_distance_C(1)=-H_fine(k_burst)]

Shift_distance_C(2)=-H_fine(k_burst)-(64+2*L-1)*HPR_pulse_SAR

Computation of the phase shift corresponding to the distance shift

The shift of distance is corrected in the time domain as it is done on-board to apply the fine component

of the tracker range for the LRM mode. To correct from this shift of distance, we use the FFT function

theorem that can be expressed by the following equation:



rc

K2f =

r being the range correction (see equations (7), (8) and (9), in this case it is the fine slant range Drslant

correction. K is the chirp slope and c the light velocity. The chirp slope K is given by

K = B/T

B being the emited bandwidth and T the pulse duration.


]t)n(rc

K2j2exp[)t,n( kerTrac−=

) 2 exp( ). ( )) ( ( fa j G TF a x G TF − = −

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n corresponds to the pulse number and t the time or abscissa of the time domain echoes.

Expressing the shift in distance in time the above equation can be written as:

]128/n*)n(tBj2exp[)t,n( samplekerTrac−=

Nsample being the sample number of the echoes in the time domain (from 0 to 127)

Apply the phase shifts to each I&Q echoes in the LRM and SAR modes



Built the power pulses from the IQ pulses

• Case of an input Ku band sequence:

For each of the 4*64 Ku-band pulses (I and Q) corrected for distance, a 128-points FFT is performed

and the I2+Q2 spectrum is derived. A FFTshift is also applied to shift zero-frequency component to

center of spectrum. The Ku-band 20 Hz Pseudo-LRM 128-points I2+Q2 spectrum is then computed by

summing the 4*64 I2+Q2 waveforms.

• Case of an input C band sequence:

The same process is applied to the 4*2 C-band pulses (I and Q) of the input sequence.

Rescaling of the waveforms to have equivalent waveforms to the LRM mode

To allow the determination of the scaling factor using the same algorithm as for the LRM mode the

waveforms are rescaled to have an equivalent number of echoes as for the LRM mode.

For that the accumulated Ku band echoes are simply divided by 4*64 and then multiplied by the

number of pulses in a tracking cycle for the Ku band LRM mode (84).

For the C band echoes, they are divided by 4*2 and then multiplied by the number of pulses in a

tracking cycle for the C band LRM mode (14).

Then, the gains applied on-board after on-board FFT are also applied to the accumulated LRM-Like

waveforms. These gains are:

"Fine trigger delay" FFT gain in tracking mode "Accumulation" FFT gain in tracking mode Gain bias

In case of generation of L1bS products, SNR estimation for PLRM Ku and C bands are computed by

averaging of samples of the first plateau of the waveforms.

2.29.4 Comments

This procedure is traditionally applied on-board for pulse-width limited altimeters.

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2.30 ALT_PHY_BAC_01 – To correct the AGC for instrumental errors

2.30.1 Heritage


2.30.2 Function

To correct the AGC values for the instrumental errors, and to provide the corresponding corrections.


2.30.3.1 Input data

• AGC


AGC correction table (applied value versus transmitted value)


• Corrected AGC

• Correction for instrumental errors on AGC


For each measurement, the input AGC value is used to access the table which correct for the instrumental

errors due to the imperfections of the on-board attenuators. This table provide the corresponding

corrected values. The corresponding corrections are derived by removing the raw value from the

corrected value.

2.30.4 Accuracy

The corrected AGC will exactly represent the value applied on-board.

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2.31 ALT_PHY_BAC_02 - To compute the scaling factors for Sigma0 evaluation

(LRM mode)

2.31.1 Heritage


2.31.2 Function

To compute the so-called "scaling factors for Sigma0 evaluation" (requested to determine the backscatter

coefficients from the on-ground retracked amplitudes at Level 2). These parameters account for the total

power of the altimeter PTR (LTM calibration parameters). Moreover, the internal calibration correction

on the backscatter coefficients are computed.


2.31.3.1 Input data

• Datation:

Altimeter time-tag

• AGC:

Corrected AGC

• Orbit:

Orbit altitude


Total power of the PTR

• Corrected AGC (attenuation) used to calibrate the PTR (from ALT_PHY_BAC_01)


Number of elementary estimates per averaged measurement Antenna gain (Ku and C bands) Emitted frequency (Ku and C bands) FFT step in tracking mode, expressed in time (Ku and C bands) and in frequency Ratio of the losses between the transmission/reception and the calibration paths (Ku and C bands) Number of pulses per waveform (Ku and C bands) Parameters used to perform the on-board PTR calibrations (Ku and C bands) :

Number of pulses used to calibrate the PTR

FFT step in PTR calibration mode (expressed in frequency)

Pre-launch calibration parameters (Ku and C bands) :


Corrected AGC (attenuation) used to calibrate the PTR

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Gains (Ku and C bands) :

"Fine trigger delay" FFT gain in tracking mode (amplitude)

"Accumulation" FFT gain in tracking mode (power)


Light velocity Earth radius

• Processing parameters (SAAD):

On-board /On-ground processing consistency factor (for LRM mode)


• Scaling factor for Sigma0 evaluation

• Internal calibration correction on the backscatter coefficient


Principle

• The radar equation applied to the altimeter may be expressed by (Ref. 1):

0ate

32e

22antt

r .L).HR.(H..64

R.t.c..G.PP

+

= (1)

where:

Pr = received power at the antenna flange Pt = transmitted power at the antenna flange Gant = antenna gain (power)

= wavelength c = light velocity

t = FFT step in time Re = earth radius

0 = backscatter coefficient H = altitude (orbit) Lat = losses due to the propagation in the atmosphere

• The transmitted power is given by:

t

SSPAt

L

PP = (2)

where:

PSSPA = peak power transmitted by the SSPA Lt = losses between the SSPA and the antenna flange

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• The waveform amplitude Pu (to be provided by a retracking algorithm at Level 2) may be expressed as a function of the received power at the antenna flange (Pr), by:

=j

tjrr

ru N.PTR.G.

L

PP (3)

where:

Lr= losses between the antenna flange and the low noise amplifier (LNA) Gr = gain of the receiver chain in radar mode between the LNA and the FFT output

PTRj = PTR samples (with a frequency step ft of the FFT in tracking mode) Nt = number of pulses used in tracking

• Combining the three previous equations, and ignoring the losses due to the propagation in the atmosphere (which will be accounted for in the level 2 processing), the waveform amplitude is given by:

0

j

tjr

r

t

SSPA

e32

e22

antu .N.PTR

L

G.

L

P.

)HR.(H..64

R.t.c..GP

+

= (4)

In this equation, some parameters as the peak power transmitted by the SSPA and the PTR, are

unknown at the time of the measurement. Assuming a slow variation of these parameters versus time,

the use of internal calibration measurements will allow the computation of the backscatter coefficient.

Indeed, the total power PPTR of the PTR (LTM calibration parameter derived from the CAL1 internal

calibration process) may be expressed as:

=k

ckcc

SSPAPTR N.PTR.G.

L

PP (5)

where:

Lc = losses between the SSPA and the LNA Gc = gain of the receiver chain in calibration mode between the LNA and the FFT output

PTRk = PTR samples (with a frequency step fc of the FFT in calibration mode) Nc = number of pulses used in calibration

• Accounting for the relationship between the PTR samples and the FFT steps in tracking and in calibration modes:

=k

kc

j

jt PTR.fPTR.f (6)

and accounting for the expression of the gains ratio:

2

t,ACCU2

t,CFA10

AGC

10

AGC

r

c

128

127.

G

1.

G

1.

10

10

G

Gt

c

=

−

−

(7)

where:

AGCc = attenuation (opposite of the amplification applied on-board to the PTR) in calibration mode

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AGCt = attenuation (opposite of the amplification applied on-board to the waveforms) in tracking mode

GCFA,t = "fine trigger delay" FFT gain in tracking mode (amplitude) GACCU,t = "accumulation" FFT gain in tracking mode (power)

The backscatter coefficient is given by:

u0 P.Scale= (7 bis)

where:

cons10

AGC2

PTR10

AGCt,ACCU

2t,CFAt

c

c

t

c

rt

e22

ant

e32

F.10.128

127.

P.10

1.

G

1.

G

1.

N

N.

f

f.

L

L.L.

R.t.c..G

)HR.(H..64Scale

t

c

+= (8)

where Fcons is the on-board / on-ground processing consistency factor (processing parameter)

The losses (Lt, Lr, Lc) and/or their ratio (Rloss = Lt.Lr/Lc) are assumed to be constant and characterized

before launch.

• The internal calibration correction on the backscatter coefficients may be expressed with respect to a prelaunch calibration, which is characterized by the following input parameters:

Total power of the PTR : prelaunchTR,PP

Corrected AGC used to calibrate the PTR : prelaunch,cAGC

Number of pulses used to calibrate the PTR : prelaunch,cN

FFT step in PTR calibration mode (expressed in frequency) : prelaunch,cf

Indeed, computing the corrected backscatter coefficient (0cor) according to (8) and computing the raw

backscatter coefficient (0raw) according to (8) where Nc, fc, AGCc and PPTR are superseded by the

corresponding prelaunch parameters, the internal calibration correction (0cal ) may be derived by:

10

AGCAGC

PTR

prelaunch,PTR

prelaunch,c

c

c

prelaunch,c

raw0

cor0cal0

cprelaunch,c

10.P

P.

N

N.

f

f−

=

= (9)

Computation of the scaling factors for the level 2 Sigma0 evaluation (Ku and C bands)

The computations steps (for each band) are the following:

• Selection of the total power of the PTR (PPTR) to be used (averaging of calibration points over a predefined window characterized by a duration before and a duration after the processed measurement).

• Computation of the scaling factors according to (8), expressed in dB, where AGCt is superseded by the corresponding input corrected AGC, and where the waveform amplitude Pu is set to 1 (i.e. to 0 dB). They represent thus the backscatter coefficient for a waveform amplitude equal to 1 (FFT power unit).

• Computation of the internal calibration corrections on the backscatter coefficient (Ku and C bands), according to (9), expressed in dB.

• Selection of the dcal calibration parameter (averaging of calibration points over a predefined window characterized by a duration before and a duration after the processed measurement).

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2.31.4 Accuracy

Regarding the instrumental losses (between the SSPA and the antenna flange, between the antenna

flange and the LNA, and between the SSPA and the LNA), the possible variation of their ratio (involved in

the expression of the backscatter coefficient) during the mission is negligible.

Losses due to the propagation in the atmosphere are ignored in the computation of the backscatter

coefficient. They will be accounted for in the level 2 processing.

The impact on the backscatter coefficient estimation of the temperature of the altimeter components is

supposed negligible.

2.31.5 References

• Ref. 1: Calibration interne de l'altimètre POSEIDON - Principe, résultats et précision CNES 86/300 - CT/DRJ/TIT/RL-HY, 06/12/86

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2.32 ALT_PHY_BAC_03 - To compute the scaling factors for Sigma0 evaluation

(SAR mode)

2.32.1 Heritage

Jason-1

2.32.2 Function

To compute the so-called "scaling factors for Sigma0 evaluation" (requested to determine the backscatter

coefficients from the on-ground retracked amplitudes) for the SAR mode. These parameters account for

the total power of the altimeter PTR (LTM calibration parameters). Moreover, the internal calibration

correction on the backscatter coefficients is computed.


2.32.3.1 Input data

• Orbit:

Orbit altitude Satellite velocity


Total power of the PTR Closest AGC (Ku) in time

• Corrected AGC (attenuation) used to calibrate the PTR


Number of elementary estimates per averaged measurement Number of Ku-band pulses per burst in SAR mode Pulse repetition frequency Antenna gain Altimeter wavelength FFT step in tracking mode, expressed in time and in frequency (1) Ratio of the losses between the transmission/reception and the calibration paths (Ku) Number of pulses per waveform estimated after multi-looking Parameters used to perform the on-board PTR calibrations (Ku):



Pre-launch calibration parameters (Ku):


(1) depends on the altimeter configuration

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Corrected AGC (attenuation) used to calibrate the PTR




Light velocity Earth radius

• Processing parameters (SAAD):

On-board /On-ground processing consistency factor (for LRM mode)


• Ku-band scaling factor for Sigma0 evaluation in the SAR mode

• Ku-band internal calibration correction on the backscatter coefficient


Principle

• The radar equation applied to the altimeter in SAR mode may be expressed for one reference surface resolution cell by (Ref. 1):

=

=

Nb

1)(R

)().(S).(G.

L..64

.PP

40

2ant

at3

2t

r (1)

where:

Pr = received power at the antenna flange Pt = transmitted power at the antenna flange Gant(θ) = antenna gain pattern (power) θ1,...,θNb = the steering angles of the Nb bursts stacked for the reference surface sample

(angles expressed with respect to the normal of the velocity vector) Nb = number of power waveforms averaged after multi-looking λ = wavelength σ0(θ) = backscatter coefficient of the reference surface sample R(θ) = distance satellite to the reference surface elevation Lat = losses due to the propagation in the atmosphere S(θ) = area of the along-track delay/Doppler cell

Some assumptions are made:

• Given the relative low variations of the incidence angle during the multi-look integration (~0.6o) we assume that the backscatter coefficient does not depend on the steering angle θ, but on the local surface properties only.

• Given the orbit altitude, we assume that the distance R between the satellite and the reference surface elevation does not depend on θ and is equal to the altitude H at the time the satellite is at zenith of the reference point.

• The antenna gain pattern is considered to follow a Gaussian within the range of Doppler beam angles:

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−

=

2sin2

0ant eG)(G (2)

where 2ln2

sin dB32

−= and 0G is the antenna gain.

• We also assume that the along-track delay/Doppler cells spanned by a reference surface location (during the integration process) have a constant area S equal to the nadir along-track resolution cell:

RangeAzi Dist.DistS =

with: PBursts

AziNV2

PRF.HDist

= (3)

and

+=

e

eRange

R

HRtcHDist (4)

where :

c = light velocity Δt = FFT step in time PRF = Pulse Repetition Frequency NpBurst = number of pulses per burst (=64) Vs = along track satellite velocity at zenith of reference point Re = Earth radius H = orbit altitude at zenith of reference point

Finally, the received power can be approximated by:

(5)

where :

=

=Nb

1

)(GG 2ant

2

Except for the radar equation, the following steps in the computation of the scaling factor for the SAR

mode are the same as those of the same function applied to the LRM mode.

Another difference concerns the fact that the AGC is not accounted for in the scaling factor. Indeed, the

waveforms are here already corrected from AGC to allow the stacking of beams coming from different

tracking cycles.

• The transmitted power is given by:

t

SSPAt

L

PP = (6)

where:

PSSPA = peak power transmitted by the SSPA

0at

43

22t

r .L.H..64

G.S..PP

=

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Lt = losses between the SSPA and the antenna flange

• The waveform amplitude Pu (to be provided by a retracking algorithm at Level 2) may be expressed as a function of the received power at the antenna flange (Pr), by:

=j

tjrr

ru N.PTR.G.

L

PP (7)

where:

Lr = losses between the antenna flange and the low noise amplifier (LNA) Gr = gain of the receiver chain in radar mode between the LNA and the FFT output PTRj = PTR samples (with a frequency step ft of the FFT in tracking mode) Nt = number of pulses used in tracking

• Combining the three previous equations, and ignoring the losses due to the propagation in the atmosphere (which will be accounted for in the level 2 processing), the waveform amplitude is given by:

0

j

jr

r

t

SSPA

at43

22

u .PTRL

G.

L

P.

L.H..64

G.S.P

= (8)

• In this equation, some parameters as the peak power transmitted by the SSPA and the PTR, are unknown at the time of the measurement. Assuming a slow variation of these parameters versus time, the use of internal calibration measurements will allow the computation of the backscatter coefficient. Indeed, the total power PPTR of the PTR (LTM calibration parameter derived from the CAL1 internal calibration process) may be expressed as:

=k

ckcc

SSPAPTR N.PTR.G.

L

PP (9)

where:

Lc = losses between the SSPA and the LNA Gc = gain of the receiver chain in calibration mode between the LNA and the FFT output

PTRk = PTR samples (with a frequency step fc of the FFT in calibration mode) Nc = number of pulses used in calibration

• Accounting for the relationship between the PTR samples and the FFT steps in tracking and in calibration modes:

=k

kc

j

jt PTR.fPTR.f (10)

and accounting for the expression of the gains ratio (considering that the attenuation in tracking mode

is already applied on the input waveforms):

10

AGC

10

AGC

r

c

t

c

10

10

G

G

−

−

= (11)

where:

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AGCc = attenuation (opposite of the amplification applied on-board to the PTR) in calibration mode

• ALT_PHY_BAC_02 eq. (8) becomes:

𝑆𝑐𝑎𝑙𝑒 = (𝜋3.𝐻4

𝐺2𝜆2.𝑆.𝐿𝑡.𝐿𝑟

𝐿𝑐.𝛥𝑓𝑡

𝛥𝑓𝑐. 𝑁𝑐 .

10𝐴𝐺𝐶𝑡10

10𝐴𝐺𝐶𝑐10 .𝑃𝑃𝑇𝑅

) . 𝐹𝑐𝑜𝑛𝑠 (12)

where :

Fcons is the on-board / on-ground processing consistency factor (processing parameter)

• ALT_PHY_BAC_02, eq. (9) remains unchanged.

2.32.4 Accuracy

Regarding the instrumental losses (between the SSPA and the antenna flange, between the antenna

flange and the LNA, and between the SSPA and the LNA), the possible variation of their ratio (involved in

the expression of the backscatter coefficient) during the mission is negligible.

Losses due to the propagation in the atmosphere are ignored in the computation of the backscatter

coefficient. They will be accounted for in the level 2 processing.

The impact on the backscatter coefficient estimation of the temperature of the altimeter components is

supposed negligible.

2.32.5 Comments

Given the relative low variations of the incidence angle during the multi-look integration (~0.6O) we

assume that the backscatter coefficient does not depend on the steering angle θ, but on the local surface

properties only.

Given the orbit altitude, we assume that the distance R between the satellite and the reference surface

elevation does not depend on θ and is equal to the altitude H at the time the satellite is at zenith of the

reference point.

The antenna gain is considered to follow a Gaussian within the range of Doppler beam angles.

We also assume that the along-track delay/Doppler cells spanned by a reference surface location (during

the integration process) have a constant area S equal to the nadir along-track resolution cell.

The speed vector is considered to be orthogonal to the nadir looking direction when computing the off-

nadir angles.

2.32.6 References

• Ref. 1: Calibration interne de l'altimètre POSEIDON - Principe, résultats et précision CNES 86/300 - CT/DRJ/TIT/RL-HY, 06/12/86

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2.33 ALT_PHY_LOC_01 - To compute surface location (SAR mode)

2.33.1 Heritage


(Raney, 1998).

2.33.2 Function

To determine reference surface locations along the satellite track corresponding to the intersection of the

Doppler beams with an estimation of the surface elevations. This reference surface mapping will be used

all along the SAR L1b processing, including the stacking of the non-coherent Doppler contributions.


2.33.3.1 Input data

• For each burst (80 Hz):

Tracker range (Ku-band)

• Orbit position and orbit time

• Satellite velocity

• Tracker range and orbit state vector (Ku-band PLRM) for first tracking cycle

• Altimeter instrumental characterization data

Burst duration Emitted frequency (Ku-band)

• Configuration data

• Parameters for orbit and surface interpolation

Universal constant Light velocity Reference ellipsoid parameters


• Reference surface positions

• Surface positions corresponding to each burst

• Orbit state vector at each reference surface location

• Tracker range interpolated at each reference surface location

• Tracker range of the burst for the closest location

• Index of the burst corresponding to the closest tracker range

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The full process described in this algorithm considers a pre-determined temporal extent of the L0 data

time series (e.g., around 2 hours).

This module first considers an initial vector of surface elevations over the ellipsoid along the ground track:

it is determined by using the on-board tracker ranges. The reference surface locations are then

determined by identifying the intersection of the Doppler beams directions with the surface sampled by

the tracker derived elevations. It consists in an iterative process starting with the input data of the first

bursts of the L0 data set.

The first surface sample of the reference locations is determined by the tracker range associated to Ku

band PLRM of the first tracking cycle (from C-band L0 data). The use of the Ku-band PLRM data allows to

locate Ku and C band SAR data approximately at the same location on the ground (see Figure 2-3).

Figure 2-3 Syncronisation of Ku and C bands measurements

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The other positions are determined through the following steps (cf.

Figure 2-4):

1. Compute the angular spacing between beams at the current position in orbit given the expression

of the Doppler frequency given by (Raney 1998):

fD = 2Vsinα/ (1)

V being the platform speed absolute value at this location and the wavelength. The azimuth

processing will give a Doppler frequency sampling given by the inverse of the burst duration B.

The angular spacing between beams at this position is then given by:

α = asin(/2V/B)

2. Determine the intersection of this beam (of direction α) with the surface, which is sampled by the

tracker derived elevations corresponding to the next burst positions. This process consists in

scanning the sampled surface until the angle of sight exceeds α. An interpolation over the surface

elevation is then performed to precisely determine the point location.

3. Apply an interpolation in time to determine the orbit state (position, velocity) associated to the

nadir surface elevation estimated in step 2.

4. Assign a range to the reference surface elevation estimated in step 2 (to be used for beams

alignment).

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5. Assign to each surface location the closest burst location tracker range. This parameter will be used

for the waveforms misalignement correction before stacking.

6. Identify the parameters of steps 3 and 4 as the current position in orbit and start again step 1.

Figure 2-4 Determination of surface sample locations

In case of generations of L1BS products, surface positions corresponding to each burst are output.

2.33.4 Accuracy

The precision and accuracy of the reference surface mapping for SAR processing strongly rely on the

quality of the L0 orbit state vector (position and velocity).

For the few hundred of meters off the nadir point, we can state that the surface elevations vector is in the

local plan defined by the orbit velocity vector and the geodetic normal. The intersection process is thus

performed in this plan.

During the fine intersection process, the location horizontal accuracy of the reference surface point relies

on the number samples used to locally interpolate the surface (e.g., Nb_Interp_Surf = 10 samples stands

for around 9 m along-track resolution cells).

2.33.5 Comments

The number of points for the spline calculation on surface samples should not exceed 10.

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2.33.6 References


5, September, 1998.

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2.34 ALT_PHY_LOC_02 - To determine Doppler beam directions (SAR mode)

2.34.1 Heritage


(Raney, 1998).

2.34.2 Function

To determine, for each burst, the angular spacings between the instantaneous zero Doppler plane and

the lines defined by the burst centre and the reference surface locations ‘observed’ within the burst

sequence.


2.34.3.1 Input data

• Orbit:

Satellite burst centre state vector Reference surface sample position vector Surface positions corresponding to each burst


Emitted frequency Pulse repetition frequency Universal constants Light velocity


• For each burst:

Doppler beam direction angles Look angles The corresponding indices of surface positions within the whole input position vector


The following steps are performed within a loop process along the burst centre state vector (starting with

the first input burst):

1. Determine the viewing angle through the maximum and minimum angles computed at the burst

centre position by using the platform velocity and the pulse repetition interval:

θmin = acos(λ/4V/PRI)

θmax = π - θmin

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V being the platform speed absolute value at the burst location and the wavelength. The azimuth

processing will give a Doppler frequency window given by the inverse of the pulse repetition

interval (PRI).

2. Select the surface reference points (64) falling into the viewing angle of step 1 and their respective

indices within the whole input vector of reference surface points.

3. Compute, for each of the reference surface locations n (n = 1 to 64) selected in step 2, the angular

spacing n by use of the burst centre location, the burst centre satellite velocity and the reference

surface point itself.

The main output of this algorithm consists in a vector of 64 angles for each burst.

Figure 2-5 Determination of Doppler beams directions

In case of generation of L1BS products, look abgles are computed from surface positions.

2.34.4 References


5, September, 1998.

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2.35 ALT_PHY_RAN_01 – To compute the tracker ranges (corrected for the USO

frequency drift)

2.35.1 Heritage


2.35.2 Function

For each elementary measurement, to compute the Ku-band and C-band corrected tracker range

estimates, accounting for the USO frequency drift. Moreover, the USO frequency correction on the

altimeter range is computed, and the tracker range rate is converted into distance versus time.


2.35.3.1 Input data

• Datation:

Altimeter time-tag

• Data type (LRM, SAR_Ku, SAR_C)

• Tracker range:

Tracker range counter (applied altitude command H0) Tracker range rate counter (applied altitude command COR2)

• USO frequency and associated time-tag (DAAD)


Nominal USO frequency: USOnom Nominal pulse repetition frequency in LRM mode: PRF_Pulsenom Nominal burst repetiton frequency in SAR mode: PRF_Burstnom Abscissa of the reference sample for tracking (Ku and C bands): Iref

FFT step in time (Ku and C bands):t Total number of pulses per tracking cycle in LRM mode (/) :Npulse Number of bursts per tracking cycle in SAR mode: Nburst Number of pulses per burst in SAR mode: Npulse_burst Number of intervals between the first (resp. last) C band and first (resp. last) Ku band pulses in SAR

mode : L Index of the 0-frequency sample

• Universal constants (SAAD) :

Light velocity: c


• Ku-band tracker range (expressed in distance)

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• C-band tracker range (expressed in distance)

• USO frequency corrections on the altimeter range (expressed in distance)

• Tracker range rates (expressed in distance versus time)


The USO frequency corresponding to each input altimeter measurement is the closest value which

precedes the altimeter time-tag. Let USO be this value.

Tracker range estimates

The 20-Hz Ku-band and C-band tracker ranges are derived from the tracker range counter (H0 expressed

in distance) corrected for the USO drift (i.e. multiplied by USOnom/USO). The tracker range counter being

referenced to the central sample of the analyzed window, the offset corresponding to the difference

between the abscissa of this central sample (I0) and the reference abscissa for tracking, is removed.

For the LRM mode and SAR mode (Ku band SAR and Ku/C PLRM):

( )

−−= t.II

USO

USOH

2

ch ref0

nom

Where H is the applied altitude command referenced to the centre of the measurement:

• For LRM mode:

pulse

pulse

N

2COR

2

1N0HH

−+=

(H0 is referenced to the 1st pulse of the tracking cycle)

• For Ku-band SAR mode :

8^2*)8^2/4

1*

2

1*2COR*burst_k0H(roundH

4

+=

H represents the coarse trigger delay and k_burst the burst number- (from 0 to 3 (constant applied

command over a burst)

• For Ku/C-band SAR PLRM mode:

SAR_Pulse_Nimp

2COR*

2

1L*2N

N

2COR

2

1N0HH burst_pulse

burst

burst−+

+−

+=

where:

H0 is referenced to the 1th burst of the tracking cycle Npulse_burst is the number of pulses per burst in the SAR mode (66) Nimp_Pulse_SAR is the number of pulses in a tracking cycle corresponding to continue emission in

SAR mode. L is the number of intervals between the first C (resp. Last) band pulse and the first (resp. Last) Ku

band pulse within a burst.

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Moreover, the 20-Hz USO frequency correction on the altimeter range (expressed in distance) is derived

from the difference between the corrected and the raw estimates of the tracker ranges.

For the LRM mode and the SAR mode Ku band and Ku/C PLRM:

−= 1

USO

USOH

2

ch nom

USO

Tracker range rate

The 20-Hz tracker range rate counters are converted into distance versus time, accounting for the nominal

pulse repetition frequency corrected for the USO variations (i.e. PRFnom.USO/USOnom).

=

nom

nom'

USO

USO

N

PRF2COR

2

ch

where:

For LRM mode: N = Npulse and nomnom Pulse_PRFPRF =

For Ku/C-bands SAR mode and PLRM: N = Nburst and nomnom Burst_PRFPRF =

2.35.4 Accuracy

• The USO frequency associated to each altimeter measurement is the closest value which precedes the altimeter time-tag. No interpolation is required due to the sampling step of USO data

• The exact processing to be performed to account for the USO frequency drift, should consist for each 20-Hz measurement :

To restore the coarse and fine trigger delays for each emitted pulse (at the PRF rythm), from the transmitted tracker range and tracker range rate

To apply the USO drift correction to the sum of the ambiguity and of the coarse trigger delay (and not to the fine trigger delay which consists of a shift of the waveforms after FFT)

To build the corrected tracker range for each emitted pulse (adding of the fine trigger delay to the corrected sum of the ambiguity and of the coarse trigger delay)

To average the corrected tracker ranges (20-Hz).

This processing requires a perfect knowledge of the on-board software. It may be simplified by applying

the USO dritf correction to the whole 20-Hz tracker range. The maximum error of this simplified approach

is equal to the maximum value of the fine trigger delay ( 2 samples i.e about 1 meter) multiplied by

the ratio of the nominal USO frequency and of the effective USO frequency (USOnom/USO).

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2.36 GEN_ENV_SUR_01 - To determine the surface type

2.36.1 Heritage


2.36.2 Function

To determine the type of the overflown surface (“open ocean or semi-enclosed seas”, “enclosed seas or

lakes”, “continental ice” or “land”) from a dedicated land/sea mask file.


2.36.3.1 Input data

• Location (1 Hz):

Latitude Longitude

• Land/sea mask file (SAAD)


• Surface type, set to “open ocean or semi-enclosed seas”, or “enclosed seas or lakes”, or “continental ice” or “land”


The latitude and longitude of the altimeter measurement are used to determine the nearest grid point in

the land/sea mask file. The surface type is thus set to the surface type reported for this nearest grid point.

2.36.4 Accuracy

The "heritage" of DTM 2000.1 goes back to the OSUJAN89 database described by Pavlis and Rapp

(Geophys. J. Int., 1990, pp. 369-378), and the JGP95E database described in Chapter 2 of the EGM96

Technical Report by Lemoine et al. (1998).

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3 Acronyms

ACQ Acquisition

AD Applicable Document

ATBD Algorithms Theoretical Baseline Definition

CAL Calibration

COG Centre Of Gravity

DAAD Dynamic Anciliary/Auxiliary Data

DAM Data Acquisition and Management

GDR Geophysical Data Record

GNSS Global Navigation Satellite System

GPRW Gain Profile Range Window

GPS Global Positioning System

HK Housekeeping

IGDR Interim Geophysical Data Record

IPF Instrument Processing Facility

IR Impulse Response

ISP Instrument Source Packets

LRM Low Resolution Mode

LTM Long Term Monitoring

MDS Measurement Data Set

MOE Medium precision Orbit Ephemeris

MWR MicroWave Radiometer

N.A. Not Applicable

NRT Near Real Time

NTC Non Time Critical

OB On-Board

PDGS Payload Data Ground Segment

PLRM Pseudo LRM mode measurements from SAR mode pulses

POD Precise Orbit Determination

POE Precise Orbit Ephemeris

PTR Point Target Response

RD Reference Document

RINEX Receiver Independent Exchange Format

RTN Real Time Navigation

SAAD Static Anciliary/Auxiliary Data

SAR Synthetic Aperture radar

SDR Sensor Data Record

SRAL SAR Radar Altimeter

STC Short Time Critical

STM Surface Topography Mission

TAI International Atomic Time

TAS Thales Alenia Space

TBC To Be Confirmed

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TBD To Be Defined

USO Ultra Stable Oscillator

End of document

Documents

Level 1b SRAL Algorithm Theoretical Baseline Definition