SVD-Based Detection of Internal Waves in SAR Irmgery

Although satellite-based SAR is sensitive enough to pick up the modulation effects of internal waves, the signal-to-noise ratio (SNR) of th-Ls observable is believed to be to() low to afford detection of enemy sukuiarines . Adaptive Software prolses that with a new interpretation of singular value decomposition, the SNR can be improved enough to allow automated detection of sukfmrine paths. While most SVD-based analyses try to isolate one or rrore rarik^ne singular planes that contain the strongly-correlated sig^als of interest, the proposed approach is to remove those planes that can be shown to contain little or no information of interest. Rissanen's MDL rretric for model order determination will guide the removal of strong interference, while a derivative of Shannon's entropy metrics will guide the rernoval of uninformatLve noise planes. This preprocessing will allow a stochastic edge detector to find the path over which a sub mrine has altered the statistical character of the waves.