期刊论文详细信息
Sensors
Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase
Kelin Lu1  Rui Zhou1 
[1] School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China;
关键词: sensor fusion;    Gaussian mixtures;    target tracking;   
DOI  :  10.3390/s16081289
来源: DOAJ
【 摘 要 】

A sensor fusion methodology for the Gaussian mixtures model is proposed for ballistic target tracking with unknown ballistic coefficients. To improve the estimation accuracy, a track-to-track fusion architecture is proposed to fuse tracks provided by the local interacting multiple model filters. During the fusion process, the duplicate information is removed by considering the first order redundant information between the local tracks. With extensive simulations, we show that the proposed algorithm improves the tracking accuracy in ballistic target tracking in the re-entry phase applications.

【 授权许可】

Unknown   

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