压缩感知理论及其在被动线列阵声纳目标探测中的应用研究

项目名称： 压缩感知理论及其在被动线列阵声纳目标探测中的应用研究

项目编号： No.61471378

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 康春玉

作者单位： 中国人民解放军海军大连舰艇学院

项目金额： 81万元

中文摘要： 复杂干扰背景下的水下目标探测、高分辨目标方位估计是目前水下作战迫切需要解决的难题，压缩感知理论的出现为解决这一难题提供了全新的思路。本项目将基于压缩感知理论，以被动线列阵声纳为研究对象，研究压缩感知理论在水下目标探测中的适应性，通过分析被动声纳接收信号的听觉域稀疏和空间域稀疏等特性，建立合适的压缩感知模型，在此基础上结合波束形成、盲源分离等技术，突破基于压缩感知模型的干扰抑制、目标方位估计和目标波形恢复等水声关键技术，实现水下目标的探测，并通过仿真数据和海上实测数据对研究的模型与方法进行验证与优化。力求在低信噪（干）比、少阵元数、少快拍数的情况下获得良好的水下目标高分辨方位估计和波形恢复性能，为复杂背景下的水下目标检测提供新的解决途径。同时，项目研究对丰富压缩感知理论，推进压缩感知理论的应用研究也具有重要的意义。

中文关键词： 压缩感知；被动声纳；目标探测；目标方位估计；信号检测

英文摘要： Underwater targets detection and high resolution direction of arrival(DOA) estimation under complex interference background are the problems which are crying for resolution in the underwater warfare. Compressed sensing theory provides a bran-new method to resolve these problems.This fund mainly studies the compressed sensing theory and its application in underwater target detection. Based on the passive line array sonar, the adaptability of the compressed sensing in underwater targets detection is first studied, and the models are proposed through analysing the auditory domain and spatial domain sparseness characteristics of the passive received signals. Then the interference suppression, target DOA estimation and target signal recovery are accomplished combining the beamforming and blind source separation with compressed sensing theory. Finally, the researched models and methods were optimized and tested by the simulated data and the recoded data at sea. The target high resolution DOA estimation and signal recovery performance of the passive line array sonar will be improved under the low signal-noise(interference) ratio, the less sensors number and the less snapshots. It will provide a novel approach to the underwater target detection under complex background. And it is very important to advance the compressed sensing theory and its application study.

英文关键词： Compressed sensing;Passive sonar;Target detection;Target Direction of arrival estimation;Signal detection