Exploiting towed array maneuvers for online maximum likelihood field directionality estimation.

Abstract

Passive estimation of the time‐varying field directionality using a towed acoustic array remains a central problem in passive sonar. Typically, array processing algorithms are designed around the assumption of a linear array and fail to take advantage of the dynamics associated with a towed array. Performance of such systems can often be complicated by left‐right ambiguities associated with the array as well as poor resolution near endfire directions. In this paper, the dynamics of the towed array are exploited allowing for left‐right disambiguation as well as improved endfire resolution. A new method for online spatial spectrum estimation is presented. The maximum likelihood (ML) of the time‐varying field is solved for using a single expectation maximization step after each received data snapshot. A multi‐source, dynamic simulation is used to illustrate the proposed algorithm’s ability to suppress ambiguous towed‐array backlobes and resolve closely spaced interferers near endfire which pose challenges for conventional beamforming approaches, especially during array maneuvers. Simulation results suggest the online ML method offers improved M‐of‐N detection performance over that of conventional beamforming. [This work was supported by ONR.]