量测驱动的自适应似然无源弱目标跟踪  

Measurement-driven adaptive likelihood passive weak target tracking

作　　者：齐滨[1,2,3,4] 田金 邹男 梁国龙 QI Bin;TIAN Jin;ZOU Nan;LIANG Guolong(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》2023年第5期959-970,共12页Acta Acustica

基　　金：国家自然科学基金项目(62271162,62101153);国防基础科研计划项目(JCKY2019604B001);重点实验室稳定支持项目(JCKYS2021604SSJS003)资助。

摘　　要：在随机有限集理论框架下提出相应的检测前跟踪算法,将多重信号分类(MUSIC)方法空间谱的自适应加权形式作为伪似然比函数研究了基于MUSIC的近似多伯努利滤波算法。并且针对算法对目标新生响应速度慢的问题,提出了由量测驱动的目标新生模型。仿真实验验证了研究算法相比传统算法在低信噪比下有更好的跟踪性能,更少的计算量,且改进的新生模型能显著加快算法对新生目标的响应速度,响应时间缩短了50%以上。实验结果表明,所提方法鲁棒性较强,可以实现在低信噪比下对多目标的准确跟踪。Based on the theory of random finite sets,the track-before-detect for passive sonar is studied,and the adaptive weighted spatial spectrum of multiple signal classification(MUSIC)method is used as pseudo-likelihood ratio function to study the MUSICbased approximate multi-Bernoulli filtering algorithm.Aiming at the problem of slow response speed of the algorithm to target regeneration,a measurement-driven target regeneration model is proposed.The simulation results show that the proposed algorithm has better tracking performance and less computation than the traditional algorithm at low SNR,and the improved model can significantly reduce the response time of the algorithm to the new target,which is improved by more than 50%.Experimental results show that the proposed method has strong robustness and can track multiple targets accurately at low SNR.

关 键 词：无源跟踪 随机有限集 检测前跟踪 伯努利滤波 

分 类 号：TB56[交通运输工程—水声工程]