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

For many 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. This complexity in the received field causes a conventional plane‐wave beamformer to suffer a degradation in its performance. 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; however, they can exhibit excessive sidelobes for low‐SNR sources. To alleviate this problem, two high‐resolution techniques, the maximum likelihood method (MLM) and ‘‘approximate orthogonal projection’’ (AOP), or linear predictor, are applied to the simulated case of one target in white noise in a Pekeris environment. The MLM is seen to produce stable main peaks that 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.