Workshop on Mathematical Engineering IIScDRDO ISSUES

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Workshop on Mathematical EngineeringIISc-DRDOI
SSUES CHALLENGES IN AIRBORNE RADARS

• Dr A VENGADARAJAN, Sc F, LRDE

09 JUNE 2007
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• Airborne Radars being developed by LRDE
• SV 2000 Maritime Patrol Radar
• Primary Radar for AEWC
• 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

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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
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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

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Synthetic Aperture Radar

• Stripmap SAR
• Spotlight SAR
• Scan SAR
• Ground Moving Target Imaging

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SAR MODES
Scan
Stripmap
Spotlight
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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

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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

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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)

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Challenges in SAR GMTI Image Processing

• Overlay of SAR GMTI images
• Automatic Target Detection and Target
  Classification of SAR images
• SAR image processing issues

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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

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• 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

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Space time spectrum for side looking array
Radar returns are projected in both angle and
Doppler domain
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Filter requirements to remove the clutter and
jammer
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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

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FUTURISTIC REQUIREMENTS

• Knowledge Based airborne radar systems
• Signal Processing, Data Processing and Radar
  Controller Scheduler
• Cognitive Radar

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Thank You
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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
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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
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Optimal Detection and Parameter Estimation
Dechirping
Moving Target
Reference Signal
Fixed scene gives a sine Moving target still
gives a chirp
Estimate Doppler frequency and Doppler frequency
Rate
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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)
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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.