Sensor Network Approach to GPS RTK

New Navigator Seminar

20th June 2007

Nicholas Zinas

Supervisors: Prof. Paul Cross

Dr Marek Ziebart

OverviewI) The concept of Network RTK

- Network Correction Computation

- Network Correction Interpolation

- Network Correction Transmission

II) UCL RTK Software & Results

- Concept of the RTK software

- Models and Algorithms

- Results

III) Current & Future Work

- Theoretical Development

- Research Experiment

- Future Work

Overview

GPS Positioning

GPS Positioning

Absolute Positioning Relative/Differential Positioning

One Reference

StationMultiple Reference StationsPseudoRanges

Carrier Phases

&Pseudoranges

Stand Alone Precise Point Positioning

Static

Fast Static

OTF Kinematic

Stop & Go

PseudoRangesCarrier Phases &

Pseudoranges

Network

RTK

WADGPSLADGPS

CORS

Network RTK Benefits

1. Less Reference stations needed Low infrastructure Cost

2. Improved Error Modeling increased availability and reliability

3. Increased Reference Station – Rover distance separation

4. Single Receiver cm positioning lower costs

Network RTK

Network RTK

Network Correction

ComputationCorrection Interpolation Transmission of Corrections

Linear

Combination

Model

FKP VRS

Fix Network

Ambiguities

Computation

of Network

Corrections

State

Space

Observation

Space

Network RTK

Network Correction

ComputationCorrection Interpolation Transmission of Corrections

Linear

Interpolation

Algorithm

Low Order

Surface

Model

Fix Network

Ambiguities Grid Based

Parameteris

ation

Broadcast

(One way

Communication)

Bilinear

Communication

1 1 1 1 1 1( )i i i i i i

AB AB AB AB AB AB

fN dT dI

c

1 1 1 1i i i i

AB AB AB AB

fV N

c

1i

A ROVER A ROVER A ROVERV a X b Y

Models

Troposphere ESA Zenith Delay model, Global Mapping Function (GMF - Boehm et al, 2006)

Ionosphere Klobuchar Broadcast Model (double differencing, ionospheric free linear

combination)

GPS Antenna Model: IGS Antex file corrections (APC &PCV)

Geoid Model : Implementation of EGM96

RTK Software (2)

Algorithms

Point Positioning

SP3 (BRDC) orbit files implementation

LAMBDA method for Ambiguity Resolution

Reference Station Ambiguity Resolution: spanning tree algorithm, closed loop approach

Single Epoch Carrier Phase Positioning

Carrier phase and pseudorange (L1,L2,L1+L2 fixed solutions)

Multiple Epoch Carrier Phase Positioning:Helmert Blocking: Ambiguities Global Parameters, Rover position Local

(L1+L2 fixed solutions)

RTK Software (3)

Algorithms (3)

Baseline 18km (Models:None)

-0.100000

-0.080000

-0.060000

-0.040000

-0.020000

0.000000

0.020000

0.040000

0.060000

00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00

Time

De

via

tio

n f

rom

SK

I-P

RO

co

ord

ina

tes

ΔLat

ΔLong

ΔHeight

Results

Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 2 consecutive epochs

Baseline : Barking – London (OS Stations)

Results (2)

Baseline: 18 km (Models: Ionosphere,Troposphere,Antenna)

-0.080000

-0.060000

-0.040000

-0.020000

0.000000

0.020000

0.040000

0.060000

00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00

Time

Dev

iati

on

fro

m S

KI-

PR

O c

oo

rdin

ates

ΔLat

ΔLong

ΔHeight

Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 2 consecutive epochs

Baseline : Barking – London (OS Stations)

Results (3)

Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 4 consecutive epochs

Baseline : Barking – London (OS Stations)

Baseline 18km (Models: Ionosphere,Troposphere,Antenna)

-0.080000

-0.060000

-0.040000

-0.020000

0.000000

0.020000

0.040000

0.060000

0.080000

00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00

Time

De

via

tio

n f

rom

SK

I-P

RO

Co

ord

ina

tes

ΔLat

ΔLong

ΔHeight

Results (4)

Number of Satellites used in Multiple Epoch Carrier Phase Positioning

0

2

4

6

8

10

12

00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00

Time

Nu

mb

er o

f Sat

ellit

es

Satellites

Multiple Epoch Carrier Phase Positioning (L1+L2) : Maximum 4 consecutive epochs

Baseline : Barking – London (OS Stations)

Single Epoch Carrier Phase Positioning (L1+L2) (carrier phase & pseudorange)

Baseline : Barking – London (OS Stations)

Results (5)

Baseline 18km (Models: Ionosphere,Troposphere,Antenna)

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

00:00:00 04:48:00 09:36:00 14:24:00 19:12:00 00:00:00 04:48:00

T i me

Devia

tion from

SK

I-P

RO

com

pute

d C

oordin

ate

s

DLat

DLong

DHeight

Results (6)

ΔLatitude

1σ 2σ

ΔLongitude

1σ 2σ

ΔHeight

1σ 2σ

Ambiguity Success

Rate

Single Epoch

Carrier Phase

Positioning0.0091

0.0182

0.0037

0.0074

0.0162

0.0323

91%

Maximum 4

Consecutive

Epochs

(All Models)

0.0086

0.0173

0.0038

0.0076

0.0159

0.0318

57 %

Maximum 2

Consecutive

Epochs

(All Models)

0.0083

0.0167

0.0036

0.0072

0.0151

0.0302

43%

Maximum 2

Consecutive

Epochs

(No Models)

0.0102

0.0204

0.0046

0.0092

0.0186

0.0372

13%

Research Experiment (1)

CORS : 3

- 1 ZMAX Net (JGC)

- 1 Trimble NetR5 (Geot)

- 1 Trimble 4000SSI

(Dionysus Satellite Observatory)

GPS Receivers : 14

- 12 Trimble R8/5800

- 2 Trimble 5700Reference Station Networks

a) JGC-DION-S1

b) JGC-DION-GEOT

c) GEOT-DION-S1

d) JGC-DION-GEOT-S1

Dionysus Satellite Observatory

Dionysus – dion: 159.713m

Dionysus – JGC: 11604.133m

Dionysus – S1 : 22001.990m

Dionysus – Geot : 9771.100m

Research Experiment (2)

Dionysus Satellite Observatory

Research Experiment (3)

Dionysus – R12 : 789.034m

Dionysus – R11 : 20331.590m

Dionysus – R6 : 13676.251m

Dionysus – R8 : 13125.525Dionysus – R9 : 10801.607

Dionysus – R7 : 9295.421m

Dionysus – R4 : 8459.406m

Dionysus – R1 : 8309.600m

Dionysus – R2 : 7594.345m

Dionysus – R10 : 7327.178

Dionysus – R3 : 5530.964m

Dionysus – R5 : 5108.805m

Research Questions

How many users needed in order to see improvement in the computation of the

Rover position?

Does the geometry of the rovers affect the solution?

What is the Ambiguity Success Rate we can achieve in Single Epoch Carrier

Phase Positioning?

How can we take advantage of the redundancy in the equations in terms of

modelling various error sources?

Since we know the ambiguities between the users can we use this system to

determine the atmospheric influence on GPS signals in a regional level?

What is the magnitude of the improvement, if any?

Implementation of the concept in the UCL-RTK software

Test the results against GIPSY computed rover positions

Compare the position time series of R12 against single baseline RTK

positioning

Generate VRS stations for each of the rovers and compare against VRS positioning

Aim is to develop a robust centralized Network RTK positioning approach where all the appropriate steps will be carried out at a central processing facility, transmitting to the user just its final position.

Future Work