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

Quan-bo GE; Wen-bin LI; Cheng-lin WEN

doi:10.1631/jzus.C10a0353

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

计算机与自动化 | Updated：2022-08-31

- SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking
- SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking
- 信息与电子工程前沿（英文） 2011年12卷第8期页码：678-686
- Affiliations：
  
  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
- Author bio：
  
  E-mail:qbge@hdu.edu.cn
  ‡Corresponding Author
- Funds：
- DOI：10.1631/jzus.C10a0353
  中图分类号：
- 收稿：2010-07-29，
  
  录用：2011-03-03，
  
  纸质出版：2011-08
- Accepted：
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SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking[J]. 信息与电子工程前沿（英文）, 2011,12(8):678-686.

Quan-bo GE, Wen-bin LI, Cheng-lin WEN. SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(8): 678-686.
SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking[J]. 信息与电子工程前沿（英文）, 2011,12(8):678-686. DOI： 10.1631/jzus.C10a0353.

Quan-bo GE, Wen-bin LI, Cheng-lin WEN. SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(8): 678-686. DOI： 10.1631/jzus.C10a0353.

摘要

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.

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