Enhanced Multistatic Active Sonar via Innovative Signal Processing
Technical rept. 1 Jan-31 Dec 2010
FLORIDA UNIV GAINESVILLE DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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Our goal is to address fundamental signal processing research issues for enhanced multistatic active sonar systems. To effectively mitigate the reverberation problems encountered in shallow water, both probing waveform synthesis and receive filter design need to be optimized. In this report, CAN cyclic algorithm-new is employed to synthesize probing sequences with good aperiodic auto-correlation properties. The performance of the CAN sequences will be compared with those of pseudo random noise and random phase sequences. Two adaptive receiver designs, namely the iterative adaptive approach IAA and the sparse learning via iterative minimization SLIM method, will also be considered. IAA and SLIM will be compared with the conventional matched filter method. In addition, a fast implementation of the SLIM algorithm is presented by taking advantage of the conjugate gradient method and the fast Fourier transform.
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