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Front. Inform. Technol. Electron. Eng.  2011, Vol. 12 Issue (8): 678-686    DOI: 10.1631/jzus.C10a0353
    
SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking
Quan-bo Ge1,2, Wen-bin Li1, Cheng-lin Wen*,1
1 Institute of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China 2 State Key Lab of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
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Abstract  Square-root cubature Kalman filter (SCKF) is more effective for nonlinear state estimation than an unscented Kalman filter. In this paper, we study the design of nonlinear filters based on SCKF for the system with one step noise correlation and abrupt state change. First, we give the SCKF that deals with the one step correlation between process and measurement noises, SCKF-CN in short. Second, we introduce the idea of a strong tracking filter to construct the adaptive square-root factor of the prediction error covariance with a fading factor, which makes SCKF-CN obtain outstanding tracking performance to the system with target maneuver or abrupt state change. Accordingly, the tracking performance of SCKF is greatly improved. A universal nonlinear estimator is proposed, which can not only deal with the conventional nonlinear filter problem with high dimensionality and correlated noises, but also achieve an excellent strong tracking performance towards the abrupt change of target state. Three simulation examples with a bearings-only tracking system are illustrated to verify the efficiency of the proposed algorithms.

Key words： Nonlinear system      Maneuver target tracking      Correlated noises      Square-root cubature Kalman filter (SCKF)      Strong tracking filtering (STF)     
Received: 29 July 2010      Published: 03 August 2011
CLC:  TP2  
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Cite this article:

Quan-bo Ge, Wen-bin Li, Cheng-lin Wen. SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking. Front. Inform. Technol. Electron. Eng., 2011, 12(8): 678-686.

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http://www.zjujournals.com/xueshu/fitee/10.1631/jzus.C10a0353     OR     http://www.zjujournals.com/xueshu/fitee/Y2011/V12/I8/678


SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking

Square-root cubature Kalman filter (SCKF) is more effective for nonlinear state estimation than an unscented Kalman filter. In this paper, we study the design of nonlinear filters based on SCKF for the system with one step noise correlation and abrupt state change. First, we give the SCKF that deals with the one step correlation between process and measurement noises, SCKF-CN in short. Second, we introduce the idea of a strong tracking filter to construct the adaptive square-root factor of the prediction error covariance with a fading factor, which makes SCKF-CN obtain outstanding tracking performance to the system with target maneuver or abrupt state change. Accordingly, the tracking performance of SCKF is greatly improved. A universal nonlinear estimator is proposed, which can not only deal with the conventional nonlinear filter problem with high dimensionality and correlated noises, but also achieve an excellent strong tracking performance towards the abrupt change of target state. Three simulation examples with a bearings-only tracking system are illustrated to verify the efficiency of the proposed algorithms.

关键词： Nonlinear system,  Maneuver target tracking,  Correlated noises,  Square-root cubature Kalman filter (SCKF),  Strong tracking filtering (STF) 
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