Source localization in a stochastic ocean using data from the Santa Barbara Channel experiment

Abstract

Source localization performance using matched field processing is degraded when: (1) incorrect environmental information is used in replica generation; and (2) the propagation model fails to correctly predict energy transfer from one spatially derived eigenvalue to another. Krolik [J. Acoust. Soc. Am. 92] addressed (1) by developing a robust adaptive matched field processor assuming a stochastic propagation medium and a perturbed sound speed profile. Czenszak [J. Acoust. Soc. Am. 101] extended Krolik’s work to include multiple narrow-band frequencies. We approach both (1) and (2) by direct decomposition of the simulated pressure field based on environmental perturbations. This yields information on energy distribution from a single point source on spatially derived eigenvalues in a simulated environment. We will explore the application of both processors and extensions of them to range-dependent shallow water acoustic data taken from the 1998 Santa Barbara Channel experiment. Source localization performance of the stochastic ocean beamformer is contrasted with both Bartlett and White Noise Constrained processors at ranges to 15 km, with emphasis on performance metrics in the face of uncertain environmental knowledge.