Abstract

Adaptive matched-field processing (MFP) is extremely sensitive to environmental uncertainties. While conventional and adaptive techniques may work for low-frequency signals in well-studied environments, the localization performance usually degrades rapidly as frequency increases, such that MFP in the 3.5 kHz regime, in shallow water environments, is typically problematic. A broadband coherent method [IEEE J. Ocean. Eng. 21, 384–392], combined with white noise constraint and principal component techniques, is implemented to construct robust replicas from experimental data. Matched-field tomography is then used to better understand the origin of the frequency dependent MFP mismatch (uncertain bottom structure, sound speed fluctuations, or both), and the results are compared with simulations. Ultimately, we want to gain some insights into how to implement a robust matched-field processor for high-frequency scenarios without using experimental data to create replica vectors. In particular, we are seeking to understand the thresholds for adaptive processors as function of signal to noise ratio and frequency dependent environmental mismatch. [Work supported by ONR.]

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