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Open AccessArticle

Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase

by Kelin Lu * and Rui Zhou
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Author to whom correspondence should be addressed.
Academic Editor: Xue-Bo Jin
Sensors 2016, 16(8), 1289;
Received: 12 July 2016 / Revised: 5 August 2016 / Accepted: 9 August 2016 / Published: 15 August 2016
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
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. View Full-Text
Keywords: sensor fusion; Gaussian mixtures; target tracking sensor fusion; Gaussian mixtures; target tracking
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Lu, K.; Zhou, R. Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase. Sensors 2016, 16, 1289.

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