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Enhanced Multistatic Active Sonar via Innovative Signal Processing
Multistatic active sonar systems involve the transmission and reception of one or more probing sequences, which provide a basis for extraction of target information in a region of interest.The probing sequences at the transmitter and signal processing at the receiver play crucial roles in the overall system performance.CAN cyclic algorithm-new is employed to synthesize probing sequences with good aperiodic autocorrelation properties.The performance of the CAN sequences is 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, are also considered.IAA and SLIM are compared with the conventional matched filter method.The performances of the algorithms are illustrated via numerical examples, which show that CAN, IAA, and SLIM can contribute to the overall performance improvement of the active sonar systems.SUBJECT
multistatic, transmission, information, transmitter, processing, performancecan, algorithm-new, autocorrelation performance, sequencestwo, minimization, considerediaa conventional, performances algorithms, improvement systemssubject,
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