A Mixture Cauchy Kernel Based Estimation Method for INS/GNSS under GNSS-Challenged Environment

Qingwen Meng, Ming Gao, Gaungwei Wang, Lu Yang, Hailun Zhang, Jianqiang Wang

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Due to the existence of a challenged environment for intelligent vehicle position such as non-Gaussian measurement noises and sudden changes of system status, the robust forecasting-aided state estimation is pivotal for non-linear inertial navigation system/global navigation satellite system (INS/GNSS) integrated navigation system stability. In order to enhance the robustness of the conventional non-linear method utilized in the INS/GNSS system, this study introduces a robust Cubature Kalman filter (CKF) that relies on the mixture Cauchy kernel (MCK). The utilization of the greatest MCK correntropy is employed as a substitute for the mean square error loss inside a reduced CKF framework. One advantage of employing this approach is the integration of the MCK and CKF, which has been developed in the context of robust information theoretic learning to address non-Gaussian interference in GNSS data, with the CKF, which excels in handling strong model nonlinearities. Additionally, this approach ensures the computational efficiency of the algorithm. Numerical simulation results carried out on INS/GNSS nonlinearity systems validate the efficacy of the proposed methods for state estimation under various types of measurement.

源语言英语
主期刊名Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350340488
DOI
出版状态已出版 - 2023
活动7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023 - Changsha, 中国
期限: 27 10月 202329 10月 2023

出版系列

姓名Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023

会议

会议7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023
国家/地区中国
Changsha
时期27/10/2329/10/23

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引用此

Meng, Q., Gao, M., Wang, G., Yang, L., Zhang, H., & Wang, J. (2023). A Mixture Cauchy Kernel Based Estimation Method for INS/GNSS under GNSS-Challenged Environment. 在 Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023 (Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CVCI59596.2023.10397181