Performance of adaptive beamforming (ABF) for fixed receiver bistatic active systems

Abstract

Data collected from a sea test have been processed and analyzed to examine the performance of adaptive spatial beamforming techniques in fixed receiver bistatic active systems. Adaptive beamforming using both the least-mean-squared (LMS) method and block sample-matrix-inversion (SMI) method have been studied. The LMS method uses the current input signal to recursively update the adaptive weight; it converges slowly and provides only a little adaptive gain (over the conventional beamforming) for reverberation suppression. On the other hand, the SMI method uses an estimate of the current covariance matrix to recursively update the adaptive weight; it converges rapidly and provides more than 10 dB adaptive gain. It is well known that adaptive processing is very sensitive to mismatch due to system errors or environmental fluctuations. To recover the signal lost in mismatch, two robust SMI adaptive beamformers, Feedback-Loop White-Noise-Constrained (FLWNC) method and Signal-Coherence-Constrained Reduced-Rank (SCCRR) method, were applied. They successfully recover signals and maintain excellent clutter suppression.