一种适用于水下距离徙动目标的稳健自适应检测算法  

Robust Adaptive Detection Algorithm of Underwater Targets under Range Cell Migration

作　　者：宋琼 闫晟[1] 郝程鹏[1] 侯朝焕[1] SONG Qiong;YAN Sheng;HAO Cheng-peng;HOU Chao-huan(The Institute of Acoustics of the Chinese Academy of Sciences,Beijing 100190,China;School of Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院声学研究所,北京100190 [2]中国科学院大学电子电气与通信工程学院,北京100049

出　　处：《水下无人系统学报》2021年第5期533-540,共8页Journal of Unmanned Undersea Systems

基　　金：国家自然科学基金项目资助(61971412).

摘　　要：在水下目标自适应检测中,目标的高速运动会引起距离徙动(RCM)现象,从而导致检测性能下降。同时,由于水下环境的复杂性,还面临着辅助数据严重不足的问题。为解决以上问题,文中提出一种新的自适应检测算法,首先基于模型阶数选择方法,将声呐回波信号表示为多个时域序列形式,随后利用对称线阵协方差矩阵的斜对称结构对RCM目标的多元假设检验模型进行改进,进一步提出基于斜对称广义信息准则自适应匹配滤波(PG-AMF)检测算法。仿真结果显示,PG-AMF算法降低了对辅助数据的依赖,能够较为准确地估计出RCM目标回波的分布情况,进而取得良好的目标检测性能。The performance of target adaptive detectors decreases owing to range cell migration(RCM),which is caused by a target moving at high speed.When the detection occurs underwater,this environment also results in a lack of aux-iliary data.To solve this problem,this study presents a new adaptive detection algorithm.First,the sonar echo is mod-eled as multiple time-domain sequences based on the model order selection theory.Then,the multiple hypothesis testing model of the target under RCM is improved by using the persymmetric structure of the covariance matrix of the sym-metric array.Finally,a new detection algorithm based on the persymmetric generalized information criterion adaptive matched filter(PM-AMF)is developed.Simulation results show that the PM-AMF detection algorithm reduces the de-pendence on auxiliary data and accurately estimates the position of the target echo under RCM,achieving a good per-formance on target detection.

关 键 词：水下目标 距离徙动 自适应检测 多元假设检验 声呐 

分 类 号：TJ630[兵器科学与技术—武器系统与运用工程] TN911.7[电子电信—通信与信息系统]