Wind Profiler Signal & Data Processing-Anil Anant KulkarniSAMEER, IIT Campus,Powai Mumbai 400076anilakulkarni@hotmail.com

Wind Profiler Signal & Data ProcessingBackgroundSignal Processing StepsData Analysis StepData QA/QC

Wind Profiler : Basics..Clear Air Doppler RadarDetects Reflection from Turbulence and eddiesTypical frequencies used in wind profiling45-65 MHz 404-482 MHz 915-924 MHz 1280-1357.5 MHz

Wind Profiler Basics . Electromagnetic pulse is sent into the AtmosphereDetection of the signal backscattered from refractive index in-homogeneities in the atmosphereIn clear air the scattering targets are the temperature and humidity fluctuations produced by turbulent eddies Scale is about half of the wavelength for the transmitted radiation (the Bragg Condition)

Wind Profiler : Back Scatter Signals

Wind Profiler : Scattering MechanismScattering from atmospheric targets:irregularities in the refractive index of the airhydrometeors, particularly wet ones (rain, melting snow, water coated ice)Scattering from Non-atmospheric targets:birds and insects (frequency dependant) smoke plumesInterfering signals: Ground and sea clutter Aircraft and migrating birds RFI (depends on frequency band)

Wind Profiler : Scattering Mechanism When a pulse encounters a target...It is scattered in all directions.

Of interest is the signal componentreceived back at the radar.This signal is typically much weakerthan the original sent from thetransmitter and is called the "returnsignal".

The larger the target, the strongerthe scattered signal.

Wind Profiler : Scattering MechanismRefractive index fluctuations are carried out by the wind; are used as tracersIrregularities exist in a size range of a few centimeters to many meters Different methods of wind measurement used with numerous variations: SA (Spaced Antenna) DBS (Doppler Beam Swinging)Doppler shift in the backscattered signal is used to derive the wind speed and direction as function of height

Doppler Beam Swinging (DBS)

DBS method for wind vector calculations (u,v,w)Radial velocities measured with one vertical and 2 off-zenith beamsBeam-pointing sequence is repeated every 1-5 minutesElectronic beam pointing with phase shifters using one antenna Local horizontal uniformityof the wind field is assumed

Doppler ShiftDoppler Formula: fd = - 2 *Vr / Doppler Measurement of wind speed based on the Doppler shift in the received signal: where Vr is the radial velocity of the scatterers Examples of Wind Profiler Doppler shift (radial velocity 10m/s)50MHz, wavelength 6m, Doppler shift 3.34Hz449MHz, wavelength 0.66815m, Doppler shift 29.9Hz1290MHz, wavelength 0.23m, Doppler shift 86Hz

Time Domain Processing (1.0) Spectral Domain Processing (2.0)Doppler Profile Analysis (3.0)Wind ProfilesRx I/PsWP Signal Processing Steps

DSP System : Data Flow DiagramPower Spectra + MomentsPower Spectra + MomentsPower SpectraRadar Control PCPost Processor PCFront End PCI DSP Card(1)PCI DSP Card(2)I & Q I/P

Time Domain Signal Processing.ADC SamplingCoherent IntegrationAffects data rate, Nyquist frequency, SNR8 bit Decoding Improving the Range ResolutionFourier TransformBroadens spectral featuresPower Spectral Computation.

Moments of the Average Doppler

Spectral Averaging Reduces data rate,improves detectabilityEstimation of Noise Level Identification of Doppler SignalsMaximum PeakConstruction of Doppler ProfileComputation of Moments and SNR

Spectral Domain Processing

Basic Signal Processing Steps

Doppler Profile Analysis:

The Doppler profiles from three beam directions from lower heights and higher heights are available as inputs To analyse input data to generate the 6 minute and hourly wind profiles. In this process the input Doppler profiles are subjected extensive quality assurance checks before generating the 6 minute and hourly wind profiles. Separation of Precipitation echoes Mode Merging Calculation of Radial velocity and height (6 min) Computation of Absolute Wind Velocity Vectors (UVW) Quality Assurance of sub-hourly velocity profiles Computation of Horizontal Wind Speed & direction (6 min) Computation of Hourly Averages

Basic Issues in Signal Processing.Signal Detection Discrimination between signal and noise. (Hildebrand/Sekhon) Are one or more non-noise signals present in spectrum?

Signal Identification Signal IdentificationIf more than one signal is detected, which one is due to the (clear (clear-air) atmospheric return? air) atmospheric return?What kind of What kind of a-priori information priori information can be used to select it?Can unwanted contamination be effectively filtered out without affecting (biasing) the desired

Identification of Doppler PeaksBasic Assumptions.

There exist temporal and spatial continuities in a time series of spectral profiles which can which can be be employed.

Echoes back-scattered from the atmosphere exhibit continuity in time and height that can restrict the search of restrict the search of signal peaks to a certain part of the spectrum.

Identification of Doppler PeaksMultiple Peak Identifications.Identify maximum 5 Spectral Peaks in each range binMark spectral peaks which are below the noise level thresholdCompute three Moments for remaining spectral peaks.Build the spectral chain across different range bins using wind shear criteria

Doppler Peak Identification continued..Challenges Identification of Atmospheric Targets but not the Clear Air echoesPrecipitation echoesIdentification Interference Signal Identification of ClutterIdentification of Non-Atmospheric TargetsBirds, Planes, non-stationary objects from near by buildings , roads (from Radar Side lobes)

Interferences.Interference from migrating birds: Birds act as large radar targets so that signals from birds overwhelm the weaker atmospheric signals This can produce biases in the wind speed and directionPrecipitation interference: During precipitation, the profiler measures the fall speed of rain dropsGround clutter: Ground clutter occurs when a transmitted signal is reflected off of objects such as trees, power lines, or buildings instead of the atmosphere. Data contaminated by ground clutter can be detected as a wind shift or a decrease in wind speed at affected altitudes.RF Interference:The RF Interference signals looks similar to the CAT echoes and some times are inseparable

Power Spectra : Vertical Beam with Precipitation echoes

Power Spectra : North Beam with Precipitation echoesDuring precipitation, the profiler measures the fall speed of rain drops

Power Spectra : East Beam with Precipitation echoes

Power Spectra Higher Heights

Power Spectra: Lower Heights

QA/ QC of Data Definition: The process of identifying and if possible eliminating inconsistent observations (outliers) Outliers: Data that are spatially, temporally, or physically inconsistent.

Recent development in QA/QCCoherent IntegrationWavelet pre-processing / No coherent integration / Low-pass filterWindowed FFT :No windowing for long time series.Spectral Averaging Statistical Averaging Method (SAM-ICRA)Signal Identification Multi-Peak Picking (MPP) / ETL Signal Processing System (SPS) /NCAR Improved Moments Algorithm (NIMA)Wind finding NCAR Winds and Confidence Algorithm (NWCA)ETL Signal Processing System (SPS)Weber/Wuertz (QC)