Coherence effects on the detection performance of quadratic array processors, with applications to large-array matched-field beamforming

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Abstract
The effect of coherence on the detection performance of quadratic array processors is examined using an exponential-power-law model for the signal wave-front correlation in an uncorrelated noise field. Detection performance is quantified by the small-signal deflection criterion, which is first reviewed in the general setting of quadratic detectors, and then applied to matched-field and optimal quadratic beamformers. It is shown that the detection performance of matched-field beamforming is substantially degraded for large arrays and typical coherence lengths. The optimal quadratic processor reduces this coherence loss, however, at a cost of greatly increased processor complexity. Several suboptimal beamformers with reduced computational load are also developed, and their detection performance is compared to that of the matched-field and optimal beamformers. One suboptimal processor, the subarray beamformer, has proved outstanding for this application in three respects: It can realize within 1 dB of optimal performance, is robust over a class of correlation functions, and entails a computational burden no greater than full-array matched-field beamforming.

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