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A new algorithm is presented for estimating the directions of arrival of signals from an unknown number of moving signal sources. The parameter space is a countable union of Cartesian products of the torus, each product space corresponding to a different number of signals reaching the sensor array. A Bayesian posterior probability measure is defined on this parameter space by combining the sensor array manifold models with the von-Mises prior on source motion. The estimates are generated empirically using a random sampling algorithm based on jump-diffusion processes and the results are presented from an implementation on a DAP510 massively parallel computer.>
Srivastava et al. (Mon,) studied this question.
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