Target Azimuth Detection Algorithm Based on Towed Line Array Shape Estimation

Abstract

The shape distortion of towed line array caused by ship steering maneuver will cause the performance of towed array sonar to decline sharply. Aiming at this problem, this paper proposes a towed line array shape estimation algorithm based on robust least squares by using the heading sensor information in the towed line array. The proposed algorithm transforms the shape estimation problem into a nonlinear optimization problem under equality constraints, and gives an iterative algorithm for the problem through the forward and backward propagation calculation method. Based on the estimated array, we improve the traditional sparse Bayesian learning (SBL) algorithm to estimate the target azimuth. The simulation results show that under the assumption that the array is parabolic, the proposed algorithm can accurately estimate the distorted array shape. When there is a large deviation in the heading sensor, the proposed algorithm still shows robust performance. At the same time, the improved SBL algorithm upgrades the array processing gain and port/starboard discrimination ability.