1. 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

2. 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

3. 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

4. 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

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

6. SAR MODES
Scan
Stripmap
Spotlight

7. 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

8. 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

9. 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)

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

11. 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

12. 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

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

14. Filter requirements to remove the clutter and jammer

15. 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

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

17. Thank You

19. 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

20. 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

21. 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

22. 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)

23. 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.