基于随机算法的抗混响目标探测方法  

A target detection method in reverberation environment based on stochastic algorithm

作　　者：刘冰 殷敬伟[1,2,3] 朱广平 郭龙祥[1,2,3] LIU Bing;YIN Jingwei;ZHU Guangping;GUO Longxiang(Acoustic Science and Technology Laboratory,Harbin Engineering University,Harbin 150001,China;Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University),Ministry of Industry and Information Technology,Harbin 150001,China;College of Underwater Acoustic Engineering,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程的大学水声技术重点实验室,黑龙江哈尔滨150001 [2]海洋信息获取与安全工业和信息化部重点实验室(哈尔滨工程大学),黑龙江哈尔滨150001 [3]哈尔滨工程大学水声工程学院,黑龙江哈尔滨150001

出　　处：《哈尔滨工程大学学报》2020年第2期277-281,共5页Journal of Harbin Engineering University

基　　金：国家重点研发计划(2018YFC1405900);国家自然科学基金项目(51779061);霍英东教育基金项目(151007);黑龙江省杰出青年科学基金项目(JC2017017);国防科技创新特区项目

摘　　要：为了解决在强混响环境下探测移动目标的问题,本文提出了一种探测方法。该方法利用了多帧数据之间的关联特性,使用随机算法对多帧数据进行线性测量,通过双边投影的方式提取了多帧数据的低秩结构从而抑制了混响,最终实现了对移动目标的探测。数值仿真和实验的结果表明该方法能在强混响的环境下准确地探测到移动目标。与传统方法相比,该方法优势明显,非常适合港口监测等混响环境严重的应用场景。In order to solve the problem of detecting a moving target under strong reverberation, a new detection method was proposed in this paper. This method takes advantage of the correlation of multi-frame data. Stochastic algorithm is used to carry out linear measurement of multi-frame data in the method. The low-rank structure of multi-frame data is extracted by bilateral projection to suppress reverberation, thus moving target detection is realized. Results of numerical simulations and an experiment showed that the proposed method can accurately detect a moving target under strong reverberation. Compared with traditional methods, this method has an obvious advantage and is very suitable for detection in serious reverberation environment such as harbor waters.

关 键 词：运动目标 主动探测 目标探测 混响 随机算法 低秩 低秩结构 低秩矩阵 

分 类 号：O427.9[理学—声学]