Precise bearing estimation for weak targets with a single vector hydrophone under strong interference

Abstract

Single-vector hydrophones face challenges in estimating weak moving target bearings under strong interference. This study introduces a method combining square-root cubature Kalman filtering with adaptive bearing interval constraints. Square-root cubature Kalman filtering optimizes initial bearing estimates, while adaptive bearing intervals together with a Gaussian window suppress directional interference. South China Sea experiments validate the method: Under conditions of broadband signal-to-noise ratio as low as approximately -2 dB present at an interference-to-signal ratio (ISR) of approximately 3 dB, this method reduces the root mean square error of bearing estimation from 121.67° to 14.72°.