非合作目标后验概率分布定位技术研究  

Research on the posterior probability distribution localization technology of non-cooperative targets

作　　者：于福建 卜宪中 汤志鹏 张博 YU Fujian;BU Xianzhong;TANG Zhipeng;ZHANG Bo(Nation Key Laboratory of Science and Technology on Underwater Acoustic Antagonizing,China State Shipbuilding Corporation System Engineering Research Institute,Beijing 100036,China;Acoustic Science and Technology Laboratory,Harbin Engineering University,Harbin 150001,China;Key Laboratory of Marine Information Acquisition and Security,Ministry of Industry and Information Technology,Harbin Engineering University,Harbin 150001,China;College of Underwater Acoustic Engineering,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]中国船舶工业系统工程研究院水声对抗技术重点实验室,北京100036 [2]哈尔滨工程大学水声技术重点实验室,黑龙江哈尔滨150001 [3]哈尔滨工程大学海洋信息获取与安全工业和信息化部重点实验室,黑龙江哈尔滨150001 [4]哈尔滨工程大学水声工程学院,黑龙江哈尔滨150001

出　　处：《应用科技》2022年第5期88-94,共7页Applied Science and Technology

基　　金：水声对抗技术重点实验室基金项目(MB91461)。

摘　　要：在水下多个非合作目标声学定位问题中,当目标声学特征未知或多个目标声学特征相似,则会存在观测数据与目标关联的困难,使得数据关联算法复杂度高、关联正确率低。针对这一问题,本文提出基于目标后验概率空间分布的水下多非合作目标定位算法。该算法首先结合定位系统确定观测区域,并将整个区域离散化,然后计算所有离散位置的目标后验概率,最后依据目标后验概率空间分布对位置离散点做筛选,对满足条件的点聚类分析,得出多目标定位结果。仿真和试验验证结果表明,该算法无需进行复杂的观测数据与目标的关联,可有效提高传统分布式定位系统对多个非合作目标的定位能力。When it comes to multiple underwater non-cooperative targets positioning,it is difficult to associate the measurement data with the targets when the acoustic characteristics of the targets are unknown or similar,resulting in high complexity of data association algorithm and low correlation accuracy.In order to solve this problem,this paper puts forward an underwater non-cooperative targets localization algorithm based on post probability spatial distribution of targets.Firstly,the algorithm determines the observed area in combination with the positioning system and discretizes the whole area.Then it calculates the posterior probabilities of all discrete positions.Finally,it screens the discrete points according to the spatial distribution of posterior probabilities of the targets and obtains the positioning results after cluster analysis for the points that satisfy the condition.Simulation and test results show that this algorithm can effectively improve the ability of traditional distributed positioning systems to locate multiple non-cooperative targets,requiring no complex measurement data and target association.

关 键 词：水声定位 遍历搜索 数据关联 聚类融合 多目标 冗余观测 被动测量 分布式定位 

分 类 号：O427.9[理学—声学]