Application of high-resolution processing to range and depth estimation using ambiguity function methods

Abstract

For many acoustic environments a target's acoustic field incident on a hydrophone array segment is not representable by a plane wave, but is a function, generally, of three coordinates: range, depth, and bearing. In these cases a conventional beamformer, which is designed to detect plane waves, cannot localize the target accurately. Techniques have been developed recently to exploit the complexity of the field to estimate the source location coordinates by correlating the received field on the array with accurate replicas of the acoustic field, derived from knowledge of the environment. The potential utility of such techniques has been demonstrated in determining range and depth for simulated high-SNR signals. In this paper, however, they are shown to exhibit excessive sidelobes for low SNR. To alleviate this problem, two high-resolution techniques, the Maximum Likelihood Method (MLM I and “Alternate Orthogonal Projection” (AOP), or linear predictor, are applied to the simulated case of one target in white noise in a Pekeris environment. MLM is seen to produce stable main peaks which localize targets precisely with low sidelobes, while AOP is shown to be unstable in the presence of random noise and to produce false peaks even when the noise fields are stable.

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