Shallow water source localization using a mobile short horizontal array

Abstract

This paper presents an approach to the challenging issue of passive source localization in shallow water using a mobile short horizontal linear array with length less than ten meters. The short array can be conveniently placed on autonomous underwater vehicles and deployed for adaptive spatial sampling. However, the use of such small aperture passive sonar systems makes it difficult to acquire sufficient spatial gain for localizing long-range sources. To meet the requirement, a localization approach that employs matched-field based techniques that enable the short horizontal linear array is used to passively localize acoustic sources in shallow water. Furthermore, the broadband processing and inter-position processing provide robustness against ocean environmental mismatch and enhance the stability of the estimation process. The proposed approach's ability to localize acoustic sources in shallow water at different signal-to-noise ratios is examined through the synthetic test cases where the sources are located at the endfire and some other bearing of the mobile short horizontal linear array. The presented results demonstrate that the positional parameters of the estimated source build up over time as the array moves at a low speed along a straight line at a constant depth.

TOA positioning algorithm of LBL system for underwater target based on PSO

“…(iii) The distance intersection positioning algorithm based on the weighted sound speed: using (2) with the SSP, we can calculate the weighted sound speed is 1 477.7 m/s. According to the TOA measurement data, the straight distance between the underwater target and the buoy can be calculated by (1). The initial value of the underwater target position can be calculated according to (21), and the underwater target position parameters can be obtained by using the Gauss-Newton method.…”

Underwater Object Localization using the Spinning Propeller Noise of Ships Based on the Wittekind Model

“…There has been considerable attention to this issue. Several methods have been developed which work not only in ideal simulations but also in feasible frameworks that include passive localization studies [4][5][6][7][8][9]. Existing passive localization methods use based on three types of measurements: time delay of arrival (TDOA), direction of arrival (DOA), and the received signal strength or energy.…”