密集杂波背景下的水下多目标跟踪方法  

Method of underwater multitarget tracking in dense clutter scenario

作　　者：张博宇 齐滨[1,2,3] 王晋晋 梁国龙[1,2,3] ZHANG Boyu;QI Bin;WANG Jinjin;LIANG Guolong(National Key Laboratory of Underwater Acoustic Technology,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]哈尔滨工程大学水声技术全国重点实验室,哈尔滨150001 [2]海洋信息获取与安全工信部重点实验室(哈尔滨工程大学),工业和信息化部,哈尔滨150001 [3]哈尔滨工程大学水声工程学院,哈尔滨150001

出　　处：《导航定位与授时》2023年第5期31-39,共9页Navigation Positioning and Timing

基　　金：国家自然科学基金(62271162)。

摘　　要：水下多目标跟踪是水声信号处理领域研究的热点和难点问题。高斯混合概率假设密度(Gaussian mixture probability hypothesis density,GM-PHD)滤波器以其高效的计算效率为解决水下多目标跟踪问题提供了保证。然而,GM-PHD滤波器在跟踪目标时需要先验已知新生目标的强度,否则其性能会出现严重退化。针对该问题,提出一种滑动窗两步初始化高斯混合概率假设密度(sliding window two step initialization GM-PHD,SWTSI-GMPHD)滤波器。将提出的滑动窗两步初始化方法嵌入GM-PHD滤波器,利用滑动窗两步初始化方法估计新生目标强度,减少杂波干扰导致跟踪结果中出现的虚假目标。仿真实验表明,在杂波密集环境下,相较于其他跟踪方法,提出方法将跟踪精度提高69.84%,52.62%和41.05%。Underwater multitarget tracking is a hot and difficult problem in the field of underwater acoustic signal processing.Gaussian mixture probability hypothesis density(GM-PHD)filter provides sufficiently good performance for multiple target tracking problem with its efficient computational efficiency.However,the target birth intensity in GM-PHD filter need to be a priori known when tracking targets,otherwise its performance will decline dramatically.Aiming at this problem,a sliding window two step initialization GM-PHD(SWTSI-GMPHD)filter is proposed.The proposed sliding window two-step initialization method,which can estimate target birth intensity,is integrated into the GM-PHD filter to avoid clutter interference leading to false targets in the tracking results.Simulation results illustrate that the proposed method improves tracking accuracy by 69.84%,52.62%and 41.05%compared to other tracking methods in a dense clutter scenario.

关 键 词：水声信号处理 水下多目标跟踪 概率假设密度 主动声呐 密集杂波环境 

分 类 号：TB566[交通运输工程—水声工程]