联合多传感器的水下多目标无源声学定位  

Underwater multi-target passive acoustic localization based on multi-sensor collaboration

作　　者：李想[1,2,3] 王燕 齐滨[1,2,3,4] 郝宇 梁国龙[1,2,3,4] 张涵[1,2,3] LI Xiang;WANG Yan;QI Bin;HAO Yu;LIANG Guolong;ZHANG Han(National Key Laboratory of Underwater Acoustic Technology,Harbin Engineering University Harbin 150001;Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University),Ministry of Industry and Information Technology Harbin 150001;College of Underwater Acoustic Engineering,Harbin Engineering University Harbin 150001;Qingdao Haina Underwater Information Technology Co.,Ltd Qingdao 266400)

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]工业和信息化部海洋信息获取与安全工信部重点实验室(哈尔滨工程大学),哈尔滨150001 [3]哈尔滨工程大学水声工程学院,哈尔滨150001 [4]青岛海纳水下信息技术有限公司,青岛266400

出　　处：《声学学报》2024年第1期16-27,共12页Acta Acustica

基　　金：国家自然科学基金项目(62271162,62101153);重点实验室稳定支持项目(JCKYS2021604SSJS003)资助。

摘　　要：在多传感器无源声学定位问题中,不同传感器接收的来自同一目标的信号均对应于此目标位置,依据这一物理基础,提出了一种基于粒子滤波的无源声学定位方法,以有效融合多传感器数据,进而提高定位性能。该方法将粒子滤波中的似然函数定义为粒子状态所对应不同传感器信号之间互相关输出的乘积。该似然函数的设计确保所提方法可以充分获取多传感器的处理增益。此外,所提方法摆脱了传统定位范式,因此可以规避传统定位范式必须面对的测量−跟踪关联问题。湖上试验表明,在强多途干扰的条件下,传统定位方法的平均定位误差为7.2 m,而所提方法的平均定位误差为1.2 m,具有更好的性能。In the problem of multi-sensor passive acoustic localization,for a specific target,the target signals received from different sensors all originate from the same target position and thus are intrinsically correlated.Based on this physical foundation,a particle filtering-based passive acoustic localization technique is proposed to effectively integrate data from multiple sensors and thereby improve localization performance.The proposed method defines the likelihood function of the particle filter as the product of the output of the cross-correlation between the signal of different sensors conditioned on the state of the particle.This likelihood function is designed to ensure that the processing gain of multi-sensors can be fully obtained.Moreover,since the proposed method is free from the traditional localization paradigm,it can circumvent the measurement-to-track associated problem faced by the traditional localization paradigm.The lake experiment indicates that under the condition of strong interference,the average localization error of the traditional localization method is 7.2 m,while the proposed method performs better with the average localization error being 1.2 m.

关 键 词：粒子滤波 检测前跟踪 无源声学定位 互相关 

分 类 号：TB56[交通运输工程—水声工程] TP212[理学—物理]