Eigenanalysis-based adaptive interference suppression for underwater target estimation

Abstract

It is generally difficult for a passive sonar system to localize a weak source due to the complexity and variability of the ocean environment, especially in the presence of strong interferences. In this paper, an eigenanalysis-based adaptive interference suppression method (EAAIS) is presented for estimating the weak source bearing. Assuming the target of interest (TOI) is in a known bearing sector, we first define a contribution ratio for each eigenvector of the cross-spectral density matrix (CSDM). The eigenvectors not dominated by the TOI are adaptively identified and removed for interference suppression. The remaining eigenvectors are then used to reconstruct the CSDM for TOI bearing estimation with adaptive beamforming methods. In comparison with the basic ECA method, the proposed method has better interference rejection capability and wider fields of application. Simulation and experimental results also show that the proposed method can achieve accurate localization estimates even in the presence of strong interferences.