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Research on Clustering and Fusion Tracking Technology of Dense Group Target
The dense maneuvering individual tracking in cluster target tracking tasks has the problems of difficult cataloging,high computational resource requirements,and complex trajectory modeling.Based on the analysis and differentiation of the motion characteristics and tracking points of dense multi-target and cluster targets,a cluster target tracking strategy based on the fusion planning of individual targets and group evolution features is proposed.By modeling the group structure and number,combined with the dynamic evolution of the group structure,the group is clustered,planned,and classified.On this basis,the shape,center,number of targets,as well as the grayscale,position and other feature information of individual targets are fused and calculated to achieve robust extraction of the tracking position of cluster targets,improve the stable tracking ability and accurate trajectory generation ability of the cluster.It mainly solves the clustering problem of group targets,the location extraction of group envelope,the location fusion problem of multiple single targets,the position switching strategy and the smooth transition problem of tracking between multiple groups or group beyond the field of view.The experimental results verify that the proposed method can effectively improve the tracking performance,the tracking accuracy is increased by 12%,the tracking stability is increased by 4 times,and the calculation amount is reduced.
Key words: Cluster; track; Integration; Group envelope; Group structure; Tracking accuracy; Tracking stability
TANG Zili , WANG Wei , WANG Weiqiang , ZHANG Hua . Research on Clustering and Fusion Tracking Technology of Dense Group Target[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2025 , 45(6) : 1318 -1325 . DOI: 10.15892/j.cnki.djzdxb.2025.06.044
| [1] |
马子玉, 何明, 刘祖均. 无人机协同控制研究综述[J]. 计算机应用, 2021, 41(5):1477-1483.
|
| [2] |
赵琳, 吕科, 郭靖. 基于深度强化学习的无人机集群协同作战决策方法[J]. 计算机应用, 2023, 43(11):3641-3646.
|
| [3] |
姜剑雄, 桂阳, 李琴. 反无人机集群态势感知应对策略研究[J]. 无人系统技术, 2024, 7(4):48-54.
|
| [4] |
|
| [5] |
杨洋, 宋品德, 钟春来, 等. 无人机视角下基于深度学习的多目标跟踪研究进展[J]. 计算机工程与应用, 2023, 59(23):48-62.
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
张峰, 田康生. 基于多假设跟踪弹道导弹主动段跟踪算法[J]. 现代防御技术, 2013, 41(3):124-132.
|
| [11] |
|
| [12] |
|
| [13] |
李振兴, 刘进忙, 李松. 一种改进的群目标自适应跟踪算法[J]. 哈尔滨工业大学学报, 2014, 46(10):117-123.
|
| [14] |
汪云, 胡国平, 刘进忙. 群目标跟踪自适应IMM算法[J]. 哈尔滨工业大学学报, 2016, 48(10):103-109.
|
| [15] |
黄剑, 胡卫东. 基于贝叶斯框架的空间群目标跟踪技术[J]. 雷达学报, 2013, 2(1):86-96.
|
| [16] |
张伟. 空间群目标下多假设跟踪方法研究[D]. 成都: 电子科技大学, 2014.
|
| [17] |
郭剑辉, 张荣涛. 弹道导弹防御中的群目标跟踪算法[J]. 计算机工程与应用, 2012, 48(35):243-248.
|
| [18] |
严灵杰, 顾杰, 姜余. 基于随机有限集的多目标跟踪技术综述[J]. 电子信息对抗技术, 2019, 39(1):81-88.
|
| [19] |
|
| [20] |
武星, 汤凯, 李兴达. 多视角雷达点云融合的移动机器人集群跟踪[J]. 仪器仪表学报, 2023, 44(12):176-185.
|
| [21] |
|
| [22] |
|
| [23] |
张瑶, 卢焕章, 张路平. 基于深度学习的视觉多目标跟踪算法综述[J]. 计算机工程与应用, 2021, 57(13):55-66.
|
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|
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