Abstract

Given well-known environmental conditions, matched field processing has been shown to be a promising signal processing technique for the localization of acoustic sources. However, when environmental data are incomplete or inaccurate, a ‘‘mismatch’’ occurs between the measured and model fields that can lead to a severe degradation of the localization estimator. The possible mismatch effects of surface and internal waves on matched field processing in a shallow water waveguide were investigated. A modified ray theory was utilized, based on the work of Tindle [J. Acoust. Soc. Am. 70, 813–819 (1981); 73, 1581–1586 (1983)], to calculate the acoustic pressure field. Thus it was possible to simply incorporate range-dependent environmental conditions as well as to generalize this work to deeper waveguides. In general, the conventional (Bartlett) matched field beamformer does not provide sufficient resolution to unambiguously locate a source, even in a perfectly matched environment. The maximum likelihood method matched field beamformer has much better resolution, but is extremely susceptible to mismatch. The mismatch due to surface roughness can result in a large reduction of the estimator peak. Part, but not all, of the peak can be regained by (1) using a model that includes incomplete reflection at the surface based on actual sea surface statistics and (2) short-time averaging of the measured signal, with times on the order of the period of the surface waves. Mismatch due to internal waves can also result in a large degradation of the estimator. Averaging over the same time period as surface waves provides little improvement and leads one to surmise that internal waves may be a limiting constraint on matched field processing. Finally, the surface and internal wave fields were combined with a slowly moving source. This example highlights the necessity for the development of a beamformer that has a broader mainlobe while maintaining adequate sidelobe suppression. This issue is addressed by looking at two such beamformers.

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