Eigenanalysis-based adaptive interference suppression

Passive sonar detection in shallow water environments is a very difficult problem when there are strong interferences. In this paper, an eigenanalysis-based adaptive interference suppression (EAAIS) method was presented. With a prior knowledge of the scope of the target's bearing, the proposed method builds a power ratio by using the beamforming of the eigenvectors of the cross-spectral density matrix (CSDM) to adaptively and robustly identify which of the eigenvectors is not dominated by the target of interest (TOI). And then the identified eigenvectors will be subtracted from the CSDM for the interference suppression. By using this approach, the residual CSDM which consists mainly of the TOI's signal is obtained and can be used in subsequent signal processing operations such as detection and localization. Numerical simulation and experimental results show that the proposed method can adaptively suppress the interferences, and effectively obtain the direction of arrival (DOA) estimates of the TOIs. In comparison with the other adaptive interference suppression methods, the proposed method has better interference suppression capability and wider range of applications without a prior knowledge of the accurate interference's bearing.