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
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;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.70