APB-1 Consumer Reports Addendum: Beam Noise Predictions for the MVSC Adaptive Beamformer
This report completes the Consumer Reports performance analysis study for the Phase 1 Advanced Processor Build sonar system. It provides a performance comparison between the conventional beamformer and the beam-based minimum variance soft constraint adaptive beamformer processing modules. Comparison was based on a beam noise output metric defined in terms of the beamformer array gain. This provides a more realistic measure of beamformer performance since, unlike the common definition of beam noise based solely on the noise field input to the beamformer, our beam noise metric factors in changes of signal power as the target signal is passed through the beamformer. Our results indicate that performance gain can be realized for the adaptive beamformer for certain scenarios. These gains were most likely to occur at the medium frequencies between 100 and 200 Hz, while significant gain was only occasionally observed at other frequencies. Adaptive beamforming was particularly successful when a clutter signal was present. However, any performance advantage usually begins to disappear as the target signal-to-noise ratio increases above approximately –15 dB.
Array Gain as a Function of SNR for the Beam-based MVSC Adaptive Beamformer
This paper examines the beam-based minimum variance soft constraint beamformer and shows that the beamformer array gain is almost always a function of SNR. The analysis shows that the MVSC array gain is necessarily a nonincreasing function of SNR and, in fact, is either strictly decreasing or constant relative to SNR. This result supplements earlier results of Van Veen and helps explain behavior observed in processed data.
Minimum variance beamforming with soft response constraints
Soft constraints on the beamformer response to the signal are examined in the context of minimum variance beamforming. A quadratic constraint on the beamformer weights is used to control the mean-squared error between a desired response and the actual response in the signal direction. The constraint is purposely chosen to permit distortion of the signal with the goal of achieving improved interference cancellation. Under the assumptions of known signal direction and spectral shape the signal-to-noise ratio is shown to be a nondecreasing function of the mean-square distortion. The distortion presented to the signal is easily computed from the beamformer weights and can be equalized after beamforming if desired. Properties of this beamforming method and its relationship to linear constrained beamforming are discussed. Simulations verify analytic results and illustrate the utility of the soft constrained approach. >