一种短垂直阵数据驱动简正波模态、波数提取方法：对称加权延拓数据矩阵SVD分解

数据驱动匹配处理是一种模基匹配处理方法，可用于水下目标定位及识别，具有先验环境信息要求少、实时性好等优点。简正波模态和波数提取方法是数据驱动匹配处理的基础。常用全水深垂直阵或长线水平阵提取模态和波数方法存在工程应用实现难的问题，亟需发展基于小孔径短垂直阵的简正波模态、波数提取方法。本项目提出《对称加权延拓数据矩阵奇异值分解》方法: 迭代构造一种新数据矩阵“对称加权延拓数据矩阵”，其奇异值分解可实现水平不变信道的简正波模态和波数提取，同时改善短阵矩阵缺秩导致的稳定性问题。本方法无需合作宽带声源，可利用机会声源或环境噪声，具有更好的工程应用前景。项目拟开展系统性理论推导，通过理论分析和数值仿真，研究方法的适用条件及其与短阵参数的关系，并开展近海原理性验证实验研究。本研究成果可为水下小平台集群查打一体化技术提供应用基础方法和技术支撑，具有重要的科学意义和应用价值。

Data-driven matching processing is a mode-based matching processing method that can be used for underwater target positioning and recognition. It has the advantages of less prior environmental information requirements and good real-time performance. The normal wave mode and wave number extraction method are the basis of data-driven matching processing. Commonly used full-depth vertical arrays or long-line horizontal arrays to extract modal and wavenumber methods are difficult to achieve in engineering applications. There is an urgent need to develop normal wave modes and wavenumber extraction methods based on small apertures and short vertical arrays. This project proposes the method of "Singular Value Decomposition of Symmetrically Weighted Extended Data Matrix": Iteratively constructs a new data matrix "Symmetrically Weighted Extended Data Matrix", whose singular value decomposition can realize the extraction of normal wave modes and wavenumbers of horizontally invariant channels. At the same time, the stability problem caused by the lack of rank of the short matrix matrix is ​​improved. The method does not need to cooperate with a broadband sound source, and can use opportunistic sound sources or environmental noise, and has a better engineering application prospect. The project intends to carry out systematic theoretical derivation, through theoretical analysis and numerical simulation, to study the applicable conditions of the method and its relationship with the parameters of the short array, and to carry out experimental research on offshore principle verification. The results of this research can provide basic application methods and technical support for the integrated technology of underwater small platform clusters, and have important scientific significance and application value.