Multiple source tracking using a high resolution method

The appropriate maximum likelihood method (AMLM) for source location estimation (SLE) allows, under certain conditions, bearing updates to be made with a very small number of snapshots, even a single one. Using these properties, the authors propose a Kalman-like algorithm, where a few new snapshots, combined with a dynamic model (either known or recursively computed) and an a priori induced distribution, allow the filter to converge in one step toward the best estimate. This property is then derived to develop recursive multiple sources tracking algorithms