DocumentCode
2820933
Title
A Nonlinear Kalman Smoothing Method for Ballistic Target Tracking
Author
Wu, Panlong ; Kong, Jianshou ; Bo, Yuming ; Li, Bing
Author_Institution
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
Volume
2
fYear
2009
fDate
24-26 April 2009
Firstpage
160
Lastpage
162
Abstract
In order to track the ballistic target more accurate, a suitable model of ballistic target motion is developed and a new nonlinear smoothing method is presented in this paper. The new nonlinear smoothing method named UKS is based on the combination of unscented Kalman filter (UKF) and Rauch-Tung-Striebel (RTS)smoothing method. The UKS method improves the tracking accuracy, and enhances the filtering convergence. The simulation of the application of UKS and UKF methods to track Ballistic target is done separately. The simulation results show that the new method outperforms UKF in terms of tracking accuracy and filter credibility.
Keywords
Kalman filters; ballistics; military computing; smoothing methods; target tracking; Rauch-Tung-Striebel smoothing method; ballistic target motion; ballistic target tracking; nonlinear Kalman smoothing method; unscented Kalman filter; Automation; Convergence; Equations; Filtering; Iterative methods; Kalman filters; Optimization methods; Radar tracking; Smoothing methods; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location
Sanya, Hainan
Print_ISBN
978-0-7695-3605-7
Type
conf
DOI
10.1109/CSO.2009.70
Filename
5193921
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