基于特征分析的自适应干扰抑制

针对水声环境中真实目标常常被强干扰掩盖而无法识别的问题,提出了一种基于特征分析的自适应干扰抑制方法(EAAIS)。根据目标信号可能的方向范围,通过构造合适的判决因子来自适应地估计并抑制互谱密度矩阵特征空间中的非目标信号子空间,得到具有更高信干比和信噪比的目标信号,为更好地实现目标识别与跟踪提供技术基础。数值仿真和海试数据验证结果表明,EAAIS方法能够自适应地抑制目标信号可能方向范围之外的强干扰,显著提高接收目标信号的信噪比和信干比,并获得更可靠的目标方位参数。相对于其它干扰抑制方法,本文提出的方法表现出了更为稳健的干扰抑制能力,具有更宽的适用条件。 

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.