Abstract

Sensor array processing methods which use full-wave models of complex multipath propagation to facilitate estimation of underwater source locations and channel parameters are known to be prone to ambiguities and environmental variability. Particularly at low signal-to-noise ratios, the performance of matched-field methods may therefore deviate radically from the Cramer–Rao bound which assumes estimation errors are small. To study matched-field processing in the presence of anomalies, this paper considers the Barankin bound. The Barankin bound is particularly useful for determining the threshold signal-to-noise ratio below which any unbiased estimate of the source location or environmental parameters will be prone to large errors. In this paper, the Barankin bound is compared with a maximum likelihood (ML) estimator of source location in an uncertain shallow-water scenario. The results indicate that the Barankin bound predicts the threshold signal-to-diffuse-noise ratio of the ML method to within 3 dB. Further, in the presence of surface shipping, the impact of both vertical and horizontal spatial decorrelation of the interference on matched-field performance is studied for different array geometries. [Work supported by ONR.]

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