一种宽带噪声信号的深海会聚区判别方法

A discrimination method for convergence zones using wideband noise signal

当目标位于不同会聚区时,其到达接收器的信号具有很强的相似特征,传统的匹配场处理模糊度表面中在不同会聚区会出现高旁瓣,当存在失配时还会导致定位错误,从而带来了难以识别目标所在会聚区的问题.本文针对会聚区判别模糊问题,根据声源在空间分布上的稀疏性,利用不同会聚区信号在频域上的起伏特征差异,基于压缩感知理论,提出了基于l1优化匹配处理的会聚区判别方法.对比传统匹配场处理方法,该方法具有高分辨性能,在有限的采样数据条件下,能有效抑制会聚区判别的旁瓣模糊问题.计算机仿真和海上拖线阵实验数据处理验证了该方法的有效性.

The strong similarity of signals from different convergence zones in deep water brings about high sidelobes in the ambiguity surface using the conventional match-field processing, which leads to localization ambiguity while the target is located in convergence zone. Aimed at the question, this paper presents a discriminate approach of convergence zone based on the l1-optimization match-field processing based on compressive sensing theory, which takes advantage of the difference in fluctuating features of received signals at different convergence zones in frequency-domain due to the sparsity of space distribution of sound source. Compared with the conventional match-field processing, the approach has a high-resolution performance and can efficiently suppress side-lobe ambiguity problem under the condition of limited sampling. The validity of the approach is verified by means of simulation and the experimental data analysis of towed array.