应用超图匹配的多假设群目标跟踪方法
发布时间：2019-04-24 21:44
【摘要】：针对群目标跟踪中的数据关联问题,本文提出一种应用超图匹配的多假设群目标跟踪方法。首先将每个群作为一个整体进行跟踪,通过引入延迟决策,利用延迟时间内产生的群航迹假设树,对群可能发生的分离与融合行为进行判断,实现对群整体的跟踪。接着考虑群内各目标通常在运动过程中将保持相对稳定的位置关系,应用超图匹配算法,由航迹与量测之间的相对位置信息辅助完成近距离群内目标的数据关联。仿真表明该多假设跟踪方法能够有效地对群结构进行估计。同时通过引入群内个体目标的相对位置信息,应用超图匹配算法能够获得更好的群内个体目标数据关联效果。
[Abstract]:In order to solve the problem of data association in group target tracking, a multi-hypothesis group target tracking method based on hypergraph matching is proposed in this paper. Firstly, each group is tracked as a whole. By introducing the delay decision and using the group track hypothesis tree generated in the delay time, the separation and fusion behavior of the group may occur is judged, and the whole group tracking is realized. Then, considering that each target in the group will keep a relatively stable position relationship during the moving process, the hypergraph matching algorithm is applied to complete the data association of the target in the close-range group with the relative position information between the track and the measurement. Simulation results show that the multi-hypothesis tracking method can effectively estimate the group structure. At the same time, by introducing the relative position information of the individual target in the group, the hypergraph matching algorithm can be used to obtain a better correlation effect of the individual target data in the group.
【作者单位】： 北京航空航天大学电子信息工程学院;景德镇陶瓷大学机械电子工程学院;
【基金】：国家自然科学基金(61471019) 航空科学基金(20152051017) 国家留学基金(201606020013)
【分类号】：TP301.6
，
本文编号：2464814
[Abstract]:In order to solve the problem of data association in group target tracking, a multi-hypothesis group target tracking method based on hypergraph matching is proposed in this paper. Firstly, each group is tracked as a whole. By introducing the delay decision and using the group track hypothesis tree generated in the delay time, the separation and fusion behavior of the group may occur is judged, and the whole group tracking is realized. Then, considering that each target in the group will keep a relatively stable position relationship during the moving process, the hypergraph matching algorithm is applied to complete the data association of the target in the close-range group with the relative position information between the track and the measurement. Simulation results show that the multi-hypothesis tracking method can effectively estimate the group structure. At the same time, by introducing the relative position information of the individual target in the group, the hypergraph matching algorithm can be used to obtain a better correlation effect of the individual target data in the group.
【作者单位】： 北京航空航天大学电子信息工程学院;景德镇陶瓷大学机械电子工程学院;
【基金】：国家自然科学基金(61471019) 航空科学基金(20152051017) 国家留学基金(201606020013)
【分类号】：TP301.6
，
本文编号：2464814
本文链接：https://www.wllwen.com/kejilunwen/ruanjiangongchenglunwen/2464814.html
