Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration

doi:10.1109/JAS.2021.1004350

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	Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration
	Lujuan Dang; Badong Chen; Yulong Huang; Yonggang Zhang; Haiquan Zhao
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2022
卷号	9 期号:3 页码:450-465
摘要	Traditional cubature Kalman filter (CKF) is a preferable tool for the inertial navigation system (INS)/global positioning system (GPS) integration under Gaussian noises. The CKF, however, may provide a significantly biased estimate when the INS/GPS system suffers from complex non-Gaussian disturbances. To address this issue, a robust nonlinear Kalman filter referred to as cubature Kalman filter under minimum error entropy with fiducial points (MEEF-CKF) is proposed. The MEEF-CKF behaves a strong robustness against complex non-Gaussian noises by operating several major steps, i.e., regression model construction, robust state estimation and free parameters optimization. More concretely, a regression model is constructed with the consideration of residual error caused by linearizing a nonlinear function at the first step. The MEEF-CKF is then developed by solving an optimization problem based on minimum error entropy with fiducial points (MEEF) under the framework of the regression model. In the MEEF-CKF, a novel optimization approach is provided for the purpose of determining free parameters adaptively. In addition, the computational complexity and convergence analyses of the MEEF-CKF are conducted for demonstrating the calculational burden and convergence characteristic. The enhanced robustness of the MEEF-CKF is demonstrated by Monte Carlo simulations on the application of a target tracking with INS/GPS integration under complex non-Gaussian noises.
关键词	Cubature Kalman filter (CKF) inertial navigation system (INS)/global positioning system (GPS) integration minimum error entropy with fiducial points (MEEF) non-Gaussian noise
DOI	10.1109/JAS.2021.1004350
引用统计	被引频次：15[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/47207
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Lujuan Dang,Badong Chen,Yulong Huang,et al. Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration[J]. IEEE/CAA Journal of Automatica Sinica,2022,9(3):450-465.
APA	Lujuan Dang,Badong Chen,Yulong Huang,Yonggang Zhang,&Haiquan Zhao.(2022).Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration.IEEE/CAA Journal of Automatica Sinica,9(3),450-465.
MLA	Lujuan Dang,et al."Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration".IEEE/CAA Journal of Automatica Sinica 9.3(2022):450-465.

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