Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration
文献类型：期刊论文
| 作者 | Lujuan Dang; Badong Chen; Yulong Huang; Yonggang Zhang; Haiquan Zhao |
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2022 |
| 卷号 | 9期号:3页码:450-465 |
| 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 |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2021.1004350 |
| 英文摘要 | 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. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/47207]  |
| 专题 | 自动化研究所_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. |
入库方式： OAI收割
来源：自动化研究所
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