PMO OpenIR  > 空间目标与碎片观测研究基地
Probabilistic Data Association Method for Space Object Tracking
Xu Zhanwei; Wang Xin
2017
发表期刊Acta Astronomica Sinica
卷号58期号:3页码:26-1-26-8
摘要In the optical tracking of space objects, multiple measurements are often detected in the observing gate, which brings about the uncertainty in the tracking accuracy and causes the unstability along the tracking path. This kind of condition will eventually interrupt the track and lead to the lost of the target. A new approach, combining the Kalman filter and probabilistic data association, is proposed for the adaptive tracking of space objects. This method employs Kalman filter to predict the gate of association, and uses probabilistic data association to obtain the equivalent measurement as an effective feed instead. The experiments show that this technique can effectively improve the tracking accuracy as well as the robustness for the automatic tracking of space objects.
语种英语
文献类型期刊论文
条目标识符http://libir.pmo.ac.cn/handle/332002/17364
专题空间目标与碎片观测研究基地
推荐引用方式
GB/T 7714
Xu Zhanwei,Wang Xin. Probabilistic Data Association Method for Space Object Tracking[J]. Acta Astronomica Sinica,2017,58(3):26-1-26-8.
APA Xu Zhanwei,&Wang Xin.(2017).Probabilistic Data Association Method for Space Object Tracking.Acta Astronomica Sinica,58(3),26-1-26-8.
MLA Xu Zhanwei,et al."Probabilistic Data Association Method for Space Object Tracking".Acta Astronomica Sinica 58.3(2017):26-1-26-8.
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