Review of the Method for Distributed Multi-sensor Multi-target Tracking

被引：0
作者：
Zeng Y. [1 ]
Wang J. [1 ]
Wei S. [1 ]
Sun J. [1 ]
Lei P. [1 ]
机构：
[1] School of Electronic and Information Engineering, Beihang University, Beijing
来源：
Journal of Radars | 2023年 / 12卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Data fusion; Distributed Multi-sensor Multi-target Tracking (DMMT); Multi-target tracking; Sensor registration; Track-to-track association;
D O I：
10.12000/JR22111
中图分类号：
学科分类号：
摘要：
Multi-sensor multi-target tracking is a popular topic in the field of information fusion. It improves the accuracy and stability of target tracking by fusing multiple local sensor information. By the fusion system, the multi-sensor multi-target tracking is grouped into distributed fusion, centralized fusion, and hybrid fusion. Distributed fusion is widely applied in the military and civilian fields with the advantages of strong reliability, high stability, and low requirements on network communication bandwidth. Key techniques of distributed multi-sensor multi-target tracking include multi-target tracking, sensor registration, track-to-track association, and data fusion. This paper reviews the theoretical basis and applicable conditions of these key techniques, highlights the incomplete measurement spatial registration algorithm and track association algorithm, and provides the simulation results. Finally, the weaknesses of the key techniques of distributed multi-sensor multitarget tracking are summarized, and the future development trends of these key techniques are surveyed. © 2023 Institute of Electronics Chinese Academy of Sciences. All rights reserved.
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页码：197 / 213
页数：16
相关论文
共 133 条
[81]  
LIAN Feng, HAN Chongzhao, LIU Weifeng, Et al., Joint spatial registration and multi-target tracking using an extended probability hypothesis density filter[J], IET Radar, Sonar & Navigation, 5, 4, pp. 441-448, (2011)
[82]  
WANG Jun, ZENG Yajun, WEI Shaoming, Et al., Multisensor track-to-track association and spatial registration algorithm under incomplete measurements[J], IEEE Transactions on Signal Processing, 69, pp. 3337-3350, (2021)
[83]  
KANYUCK A J, SINGER R A., Correlation of multiple-site track data[J], IEEE Transactions on Aerospace and Electronic Systems, AES-6, 2, pp. 180-187, (1970)
[84]  
BAR-SHALOM Y., On the track-to-track correlation problem[J], IEEE Transactions on Automatic Control, 26, 2, pp. 571-572, (1981)
[85]  
HE You, TANG Jinsong, WANG Guohong, Optimal tracking-quality-management in multiradar tracking systems[J], Modern Radar, 17, 1, pp. 14-19, (1995)
[86]  
HUANG Xiaodong, HE You, ZHAO Feng, Study of track association in typical cases[J], Journal of System Simulation, 17, 9, pp. 2085-2088, (2005)
[87]  
Lin QI, WANG Haipeng, LIU Yu, Track segment association algorithm based on statistical binary thresholds[J], Journal of Radars, 4, 3, pp. 301-308, (2015)
[88]  
HONG Shuaixin, PENG Dongliang, SHI Yifang, Track-to-track association using fuzzy membership function and clustering for distributed information fusion[C], The 37th Chinese Control Conference, pp. 4028-4032, (2018)
[89]  
AZIZ A M., A new fuzzy clustering approach for data association and track fusion in multisensor-multitarget environment[C], 2011 IEEE Aerospace Conference, pp. 1-10, (2011)
[90]  
XU Yasheng, DING Chibiao, REN Wenjuan, Et al., Multi-feature combination track-to-track association based on histogram statistics feature[J], Journal of Radars, 8, 1, pp. 25-35, (2019)
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