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• W2518542375 startingPage "1289" @default.
• W2518542375 abstract "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." @default.
• W2518542375 created "2016-09-16" @default.
• W2518542375 creator A5016554797 @default.
• W2518542375 creator A5082994943 @default.
• W2518542375 date "2016-08-15" @default.
• W2518542375 modified "2023-10-13" @default.
• W2518542375 title "Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase" @default.
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• W2518542375 doi "https://doi.org/10.3390/s16081289" @default.
• W2518542375 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5017454" @default.
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• W2518542375 hasPublicationYear "2016" @default.
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