Target Localization for a Distributed SIMO Sonar With an Isogradient Sound Speed Profile

A distributed single-input multiple-output (SIMO) sonar system makes use of a sound source and a distributed star receiver network to localize targets. Compared with the terrestrial target localization, there are more challenges for underwater target localization. The underwater sound speed varies with depth, temperature, and salinity. As a result, the propagation path of the acoustic signal is not a straight line. It makes existing straight-line based distance measurements less accurate. Furthermore, time synchronization, which is closely related to time-based localization, has to be carried out because of the absence of GPS and clock differences of underwater devices. In this paper, we take the sound speed variation and time synchronization into account and propose two underwater target localization algorithms, namely, the space-alternating generalized expectation maximization-based underwater target localization (SAGE-UTL) and the nonlinear weighted least squares based underwater target localization (NWLS-UTL), for the distributed SIMO sonar system. The SAGE-UTL algorithm is designed for the situation, where the central receiver of the star receiver network needs to remain silent for its own safety. On the other hand, the NWLS-UTL algorithm is designed for the other situation, where the silence of the central receiver is not required. We assume that all the receivers are not synchronized, and the speed variation can be approximately modeled by a depth-dependent sound speed profile. Our proposed algorithms can jointly achieve target localization and time synchronization. We evaluate the SAGE-UTL and the NWLS-UTL algorithms with several numerical simulations. The results show good performance of our proposed algorithms compared with the Cramor Rao bound and the tailored benchmark algorithms, such as the approximate nonlinear least squares algorithm and the approximate space-alternating generalized expectation maximization based underwater target localization algorithm.