Abstract
A novel approach to 3D localization of narrowband acoustic sources in a shallow ocean using a horizontal array of acoustic vector sensors (AVS) is proposed. It is shown that, if the number of sources J is known, the maximum likelihood (ML) estimates of 3/ source parameters (azimuth angles, ranges and depths) can be found in two successive stages - a J dimensional search for azimuth angles in the bounded parameter space [0 2pi]J, followed by an ML estimation of source amplitudes to obtain source range and depth. When J is not known, a stochastic search based on reversible jump Markov chain Monte Carlo (MCMC) strategy is proposed, which effectively performs the dual task of joint estimation of the number of sources and their location parameters.
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