Dr A VENGADARAJAN, Sc ‘F’, LRDE Workshop on Mathematical Engineering IISc-DRDO ISSUES & CHALLENGES IN AIRBORNE RADARS Dr A VENGADARAJAN, Sc ‘F’, LRDE 09 JUNE 2007

Airborne Radars being developed by LRDE SV 2000 Maritime Patrol Radar Primary Radar for AEW&C Synthetic Aperture Radar for UAV application with road map to extend it to other aircrafts Active Electronically Scanned Array (AESA) for Fire Control Radar – Multi Mode Radar

Common requirements of various airborne radars Look up mode (air-to-air operations – detection & tracking) Look down modes (air-to-air operations – detection & tracking) Look down mode (air-to-ground operations – detection & tracking) Look down mode (mapping operations) Look down mode (Ground ranging) Look down mode (Air to Sea operations – detection & tracking) Radar to operate in multiple modes using Low, Medium & High PRF

Detection & Tracking Requirement Clutter spreads in the Doppler domain due to platform motion Waveform optimization to maximize detection of targets against background clutter For various modes of operation For various height of operation For various clutter regions

Synthetic Aperture Radar Stripmap SAR Spotlight SAR Scan SAR Ground Moving Target Imaging

SAR MODES Scan Stripmap Spotlight

Challenges in Synthetic Aperture Radars Platform Motion Compensation (PMC) Transfer alignment of master-slave navigation system Data derived motion compensation – Auto-focus techniques Spotlight SAR Compensation for motion Through Range Cells (MTRC) GMTI

Challenges in Synthetic Aperture Radars (Ground Moving Target Imaging) Detection of Ground moving Targets - low velocity (relative) targets Conventional MTI cannot serve the purpose as these targets gets submerged in the Main Lobe Clutter

Different Ground Moving Target Indication and Detection Methods Prominent point identification method Block Matching Algorithm Detection and parameter estimation (a) Without Time Frequency Analysis (b) With Time Frequency Analysis Displaced Phase Center Antenna Space Time Adaptive Processing (STAP)

Challenges in SAR + GMTI Image Processing Overlay of SAR & GMTI images Automatic Target Detection and Target Classification of SAR images SAR image processing issues

SPACE TIME ADAPTIVE PROCESSING Applicable for both conventional radars as well as for GMTI operation in SAR Possible to detect very low velocity targets through two dimensional processing

Space Time Adaptive Processing STAP refers to the adaptive processing algorithms that simultaneously combine the signals from the elements of an array antenna (spatial) and the multiple pulses of a coherent radar waveform (temporal). Possible and required whenever there exists a functional dependency between the spatial and temporal variable. Moving Pulse Doppler Radar : Dependency of the clutter Doppler frequency on the Direction of arrival; Where  is the azimuth angle  is the elevation angle

Space time spectrum for side looking array Radar returns are projected in both angle and Doppler domain

Filter requirements to remove the clutter and jammer

Challenges in STAP Reduced Data Processing towards easing the computational complexity Requirement of massively parallel processing for real time processing Requirement of new STAP algorithm to provide for realistic (non-Gaussian, heterogeneous) clutter cancellation Generation of simulated/measured data STAP for Medium and High PRF operation under non-side looking conditions. Sub aperture based STAP

FUTURISTIC REQUIREMENTS Knowledge Based airborne radar systems Signal Processing, Data Processing and Radar Controller & Scheduler Cognitive Radar

Thank You

Prominent Point Identification Method This method is applicable only to Spotlight SAR mode. Compensates for translational and rotational motions between SAR antenna phase center and the target. In the first stage the relative translation between the radar and the target is estimated and its effect eliminated. In the second stage, the rotation rate of the target is estimated by choosing a second prominent point, compressing its signal history in range, tracking the motion of this point in the phase history. These two stages results in the complete focussing of the target Initial Scene Center Moving Target Moving target not at the scene center Moving target at the scene center

Block Matching Algorithm Generates images at different times of the same location. Therefore the clutter background appears static whereas the positions of moving target changes from image to image. Detection and estimation of target velocity and position is done Candidates for moving target are done according to signal amplitude Then a maximum-likelihood estimation of velocity and position is performed. The velocity of a candidate is obtained by estimating displacement vectors in pairs of two successive single look images by block matching algorithm. Shift of displacement vector in two images Position of tgt in image 1 Position of tgt in image 2

Optimal Detection and Parameter Estimation Dechirping fD t Fixed scene Moving Target Sine Output Doppler filter bank Moving Target Reference Signal Fixed scene gives a sine Moving target still gives a chirp Estimate Doppler frequency and Doppler frequency Rate

Displaced Phase Centre Antenna (Two element, two pulse case) PRF is chosen such that aircraft moves by one inter element spacing for each pulse Clutter cancellation is done by subtracting the second echo at first antenna (c21) from first echo at second antenna (c12)

Space Time Adaptive Processing This approach uses processing in both the time and spatial domain. Till now the algorithms were based upon the first order statistical characteristics of the echo. But STAP uses the second order statistics. This is because the determination of a target in a particular cell is no longer confined to a look into a linear array of cells, rather the targets are determined using information about adjacent cells in both dimensions.