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Adaptive Array Processing

Adaptive Array Processing. Naval Physical and Oceanographic Laboratory - Cochin Defense Research and Development Organization Ministry of Defense Govt. of INDIA. Main Beam. Side Lobes. Target Detection - Beamforming. Target’s Acoustic Radiation Directional Sea Noise

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Adaptive Array Processing

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  1. Adaptive Array Processing Naval Physical and Oceanographic Laboratory - Cochin Defense Research and Development Organization Ministry of Defense Govt. of INDIA

  2. Main Beam Side Lobes Target Detection - Beamforming • Target’s Acoustic Radiation • Directional • Sea Noise • Omni- directional Hull Mounted Array Towed Array SPATIAL FILTERING T4 T5 Receiver Array T1 T2 T3

  3. High Resolution Broadband Array Processing (MVDR) Challenges and Solutions Analytic Study And Simulation • Beam Response and Array Gain • Robust and Real Time Matrix Inversion • Derivative Constraint MVDR • Heterogeneous Response of Sensors • Array calibration techniques • Spatial Smoothing for Multipath mitigation • Diagonal Loading for Robust Response • Dynamic variations in array geometry System Implementation

  4. Adaptive Weights • Narrow Beam Width • Side Lobe Suppression • Pre-Fixed Weights • Wide Beam Width • Side Lobes MINIMUM VARIANCE DISTORTIONLESS RESPONSE (MVDR) P O W E R BEARING DEG BEARING DEG ADAPTIVE BEAMFORMER ADAPTIVE BEAMFORMER CONVENTIONAL BEAMFORMER

  5. Adaptive weights • Side lobe suppression • Beam width is array length independent • Interference suppression MVDR minimizes the variance, Subjected to the constraint, Minimum Variance Distortion less Response (MVDR) Beam Output MVDR Weights , Steering Vector

  6. No. of Operations = O (N2) MVDR BEAMFORMER : IMPLEMENTATION ISSUES & SOLUTIONS • Square Root Algorithm • Unitary Transformation • Givens Rotation • Householder Transform • Recursive update

  7. LAB EXPERIMENTS INS SAGARDHWANI- OFF PORBANDER INS SHARDA - OFF KOCHI MVDR BEAMFORMER FIELD EXPERIMENTS

  8. SCR SIR 100 m Ethernet Cable PC Based Processing & Display HUMSA Cabinet Cylindrical Array Beamforming INS DUNAGIRI – OFF BOMBAY INS BETWA – Kochi – Bombay

  9. RESULTS OF EXPERIMENTS ONBOARD INS SHARDA MVDR Beamformer Conventional Beamformer RESULTS OF EXPERIMENTS ONBOARD INS DUNAGIRI MVDR Beamformer Conventional Beamformer Time Bearing- Degree Bearing- Degree

  10. 90 90 50 50 120 60 120 60 40 40 Interferences 1 Interferences 1 30 30 150 30 150 30 20 20 10 10 Interferences 2 180 0 180 0 Steering angle Steering angle 210 330 210 330 Interferences 2 240 300 240 300 270 270 MVDR BEAM RESPONSE When steered towards the desired direction θ1, the beam pattern is given by a) Non coherent interference b) Coherent interference SOLUTION : SPATIAL SMOOTHING !

  11. Decorrelation Coherent Sources- Spatial Smoothing • R is spatially smoothed correlation matrix • RK-sub array correlation matrix • p is number of sub arrays • Ms is number of sensors of sub array • Spatially smoothed R matrix becomes non singular when the number of sub arrays is greater than the number of coherent sources • Coherent sources are effectively decorrelated • Spatial response nulls in both Coherent and non-coherent interference

  12. Derivative Constrained MVDR DC MVDR MVDR

  13. Future Work • Robust Beamforming in the presence of array deformity • Array Shape Estimation during maneuver • Left – Right Ambiguity Resolution of Linear Array • Beamforming of arbitrary distributed sensors • Space Time Adaptive Processing for SONAR • Source localization and tracking with distributed sensor networks Research Proposals for Joint Work

  14. CBF Vs ADAPTIVE MVDR BEAMFORMER CONVENTIONAL BEAMFORMER Fixed Response Adaptive Response

  15. DI (dB) F Array Gain of MVDR Beamformer

  16. Comparison of MVDR and HUMSA Display TRIAL ON INS BETWA – JAN 2007

  17. EXPERIMENT AT ACOUSTIC TANK FACILITY

  18. Bearing Time Spatial Smoothing - Experimental Results

  19. q-1 sources coherent with source 1 • One eigen value corresponds to signal sub spaces (q sources) • M-1 correspond to noise sub space • Null is not formed towards coherent interferences • q non-coherent sources and M sensors • ‘q’ eigen values correspond to signal sub space (q sources) • M-q correspond to noise sub space • Null is formed towards all interferences

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