Performance Analysis of Matched-Field Source Localization Under Spatially Correlated Noise Field

Matched-field processing (MFP) concerns estimation of source locations by exploiting full wave modeling of acoustic waveguide propagation. Typical MFP performance demonstrates a threshold behavior, that is, below some signal-to-noise ratio (SNR), the mean-square error (MSE) increases dramatically. This threshold phenomenon has been intensively investigated previously under spatially white noise field. In this paper, we develop approaches to study MFP performance in the presence of spatially correlated noises. Both the discrete interference and surface-generated noise are considered, and a so-called method of intervals errors (MIE) is derived in the context of the maximum likelihood estimate (MLE). Performance analysis of both narrowband and broadband MFP is implemented for source localization in a realistic shallow water environment. Simulation results suggest that 1) adding either spatially correlated noise increases the MLE threshold SNR compared to the case with white noise only, but effects at high SNR are different, MSE decreasing at the same rate with a point interference while decaying in a slower pace with surface-generated noises; 2) with a strong discrete interference, interference position, rather than strength, matters more in determining the MLE performance, and broadband processing effectively reduces the threshold SNR; 3) effect of the surface-generated noises is highly frequency dependent, and processing using a higher frequency would be preferred; 4) overall the surface-generated noise is more difficult to attack by an adaptive method such as the MLE.

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