模态信息非完备采样下被动声纳目标检测方法研究

项目名称： 模态信息非完备采样下被动声纳目标检测方法研究

项目编号： No.51479169

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 其他

项目作者： 孙超

作者单位： 西北工业大学

项目金额： 84万元

中文摘要： 与基于模态信息的水下目标定位问题相同，当模态信息采样不完备时，基于海洋声环境所设计的水下目标检测器的检测性能将显著下降。然而，模态信息非完备采样下的研究重点一直以来停留在模态系数的估计问题上，该因素对水下目标检测器会产生何种影响，以及如何克服或者利用该影响以恢复或者提高检测性能，是尚未开展但却值得深入研究的问题。这也是本申请项目重点研究的问题。 本项目研究步骤如下：针对水下远程低频窄带声源，结合简正波模型建立垂直线列阵接收信号的空时模型，根据经典统计信号处理理论构建相应的广义似然比检测器；通过蒙特卡洛实验方法，以及采用特征分解技术对广义似然比检测器进行处理，分析模态信息非完备采样对该检测器的影响；并结合对角加载、特征值截断、子检测器加权等方法对广义似然比检测器进行改进，最后，根据检测器的稳健性、可实现性、检测性能等指标给出一种最优的检测器改进方法。最终为声呐系统检测性能的改善奠定基础。

中文关键词： 模态信息；非完备采样；目标检测

英文摘要： Similar to the underwater passive localization problem based on modal information samples, underwater detectors designed based on the combination of acoustic modelling and sensor array sampling also suffer from performance degradation when the modal sampling information is incomplete. However, almost all the exsiting research in information sampling incompleteness focus on the modal parameter estimation problem rather than elaborating on the detection issues. Therefore, what impacts will be imposed on the detectors by the incompleteness of modal sampling and how to overcome or make use of them to restore or improve the detection performance, are worthy of in-depth research and are also the emphases of this proposed project. The project will be carried out as follows: 1) the spatial-temporal receiving signal model for the long-range narrow band acoustic source of low frequency will be established based on the normal model, and the corresponding generalized likelihood ratio test (GLRT) detector will be derived under the criterion of Neyman-Person; 2) the impacts of incomplete modal sampling on the detectors will be investigated via eigen decomposition of the GLRT detector and the Monte-Carlo experiment method; 3) according to the above analysis, the methods based on the truncated eigenvalue decompostion, the diagonal loading, and the weighting method of spectrum components to improve the detection performance will be proposed, respectively. The improved detectors will be compared with each other in terms of its robustness, realizability and detection probabilty in the same parameter scenarios, and the optimum improved method will be obtained.

英文关键词： modal information;incomplete sampling;target detection