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Sensors 2018, 18(12), 4335; https://doi.org/10.3390/s18124335

Hybrid Adaptive Cubature Kalman Filter with Unknown Variance of Measurement Noise

1
College of Intelligent Manufacturing and Automation, Henan University of Animal Husbandry and Economy, Zhengzhou 450011, China
2
Information Technology Center, Zhejiang University, Hangzhou 310027, China
3
College of Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China
4
School of Information Engineering, Zhengzhou University, Zhengzhou 450000, China
5
School of Business, University of Shanghai for Science and Technology, Shanghai 200093, China
*
Authors to whom correspondence should be addressed.
Received: 23 September 2018 / Revised: 13 November 2018 / Accepted: 27 November 2018 / Published: 7 December 2018
(This article belongs to the Collection Multi-Sensor Information Fusion)
PDF [468 KB, uploaded 7 December 2018]

Abstract

This paper is concerned with the filtering problem caused by the inaccuracy variance of measurement noise in real nonlinear systems. A novel weighted fusion estimation method of multiple different variance estimators is presented to estimate the variance of the measurement noise. On this basis, a hybrid adaptive cubature Kalman filtering structure is proposed. Furthermore, the information filter of the hybrid adaptive cubature Kalman filter is also studied, and the stability and filtering accuracy of the filter are theoretically discussed. The final simulation examples verify the validity and effectiveness of the hybrid adaptive cubature Kalman filtering methods proposed in this paper.
Keywords: nonlinear system; hybrid adaptive filtering; weighted fusion estimation; square-root cubature Kalman filter; information filter nonlinear system; hybrid adaptive filtering; weighted fusion estimation; square-root cubature Kalman filter; information filter
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Shi, Y.; Tang, X.; Feng, X.; Bian, D.; Zhou, X. Hybrid Adaptive Cubature Kalman Filter with Unknown Variance of Measurement Noise. Sensors 2018, 18, 4335.

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