The noise sound sources localization method used in shallow water is proposed. The proposed method establishes the array signal model according to the characteristics of the underwater acoustic multi-path channel, and makes use of the mult-path information and the coherent matched idea to construct the spatial focused steering vector which is in accordance with the actual sound propagation characteristics. As a result, the proposed method can not only overcome the multi-path effect but also improve the localization accuracy.Furthermore,we take the ideas of the focused beamforming based on the worst-case performance optimization for reference,and impose constraint conditions on the actual focused steering vectors to improve the optimum weight vectors and spatial spectrum form. It turns out that this method involves a quadratic minimum problem subject to non-linear constraints. Through the discussion and analysis of the spatial spectrum structure,localization errors, - 3dB beamwidth,peak and sidelobe ratio (PSR), we present the relationships between the constraint parameter choices and the mismatch errors. It is proved that the proposed algorithm can improve the robustness of the high resolution method MVDR( Minimum Variance Distortionless Response), and obtain sharper spectrum peaks and better noise interference suppression ability.%本文在建立符合水声相干多途信道特点的阵列信号模型的基础上,提出了基于多途模型匹配的浅海噪声源聚焦定位方法.该方法在本质上利用了基于模型和数据匹配的相干处理思想,充分利用了多途信道信息,生成与实际声传播特性相匹配的空间聚焦导向矢量,从而有效克服了多途效应的影响,提高了定位精度.进而结合基于最差性能优化的稳健聚焦处理器设计方法,对空间聚焦导向矢量实施约束,并划归为具有单一非线性约束的二次最小化问题,求解最优权矢量,修正得到新的空间谱形式.通过对空间谱、定位误差、-3dB波束宽度及主峰与最大旁瓣比性能进行对比分析,讨论了约束参数选取与失配误差程度之间的关系,并证明了新算法在存在失配误差的情况下,可有效提高MVDR(Minimum Variance Distortionless Response)高分辨算法的稳健性,保持较尖锐的谱峰及较强的背景起伏抑制能力.
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