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| Content Provider | Springer Nature Link |
|---|---|
| Author | Ge, Quan bo Li, Wen bin Wen, Cheng lin |
| Copyright Year | 2011 |
| 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. |
| Starting Page | 678 |
| Ending Page | 686 |
| Page Count | 9 |
| File Format | |
| ISSN | 18691951 |
| Journal | Journal of Zhejiang University SCIENCE C |
| Volume Number | 12 |
| Issue Number | 8 |
| e-ISSN | 1869196X |
| Language | English |
| Publisher | SP Zhejiang University Press |
| Publisher Date | 2011-08-02 |
| Publisher Place | Heidelberg |
| Access Restriction | Subscribed |
| Subject Keyword | Nonlinear system Maneuver target tracking Correlated noises Square-root cubature Kalman filter (SCKF) Strong tracking filtering (STF) Computer Science Communications Engineering, Networks Electronics and Microelectronics, Instrumentation Computer Hardware Computer Systems Organization and Communication Networks Electrical Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Engineering |
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