Fault-tolerant relative navigation based on Kullback–Leibler divergence
A fault-detection method for relative navigation based on Kullback–Leibler divergence (KLD) is proposed. Different from the traditional χ 2 -based approaches, the KLD for a filter is following a hybrid distribution that combines χ 2 distribution and F -distribution. Using extended Kalman filter (EKF...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2020-12-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/1729881420979125 |
| _version_ | 1818594977426440192 |
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| author | Jun Xiong Joon Wayn Cheong Zhi Xiong Andrew G Dempster Shiwei Tian Rong Wang Jianye Liu |
| author_facet | Jun Xiong Joon Wayn Cheong Zhi Xiong Andrew G Dempster Shiwei Tian Rong Wang Jianye Liu |
| author_sort | Jun Xiong |
| collection | DOAJ |
| description | A fault-detection method for relative navigation based on Kullback–Leibler divergence (KLD) is proposed. Different from the traditional χ 2 -based approaches, the KLD for a filter is following a hybrid distribution that combines χ 2 distribution and F -distribution. Using extended Kalman filter (EKF) as the estimator, the distance between the priori and posteriori data of EKF is calculated to detect the abnormal measurements. After fault detection step, a fault exclusion method is applied to remove the error observations from the fusion procedure. The proposed method is suitable for the Kalman filter-based multisensor relative navigation system. Simulation and experimental results show that the proposed method can detect the abnormal measurement successfully, and its positioning accuracy after fault detection and exclusion outperforms the traditional χ 2 -based method. |
| first_indexed | 2024-12-16T11:08:41Z |
| format | Article |
| id | doaj.art-81caf60ce8704d37975cb10737d8935b |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-16T11:08:41Z |
| publishDate | 2020-12-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-81caf60ce8704d37975cb10737d8935b2022-12-21T22:33:47ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142020-12-011710.1177/1729881420979125Fault-tolerant relative navigation based on Kullback–Leibler divergenceJun Xiong0Joon Wayn Cheong1Zhi Xiong2Andrew G Dempster3Shiwei Tian4Rong Wang5Jianye Liu6 College of Automation Engineering, , Jiangning, Nanjing, China School of Electrical Engineering and Telecommunications, , Sydney, Australia College of Automation Engineering, , Jiangning, Nanjing, China School of Electrical Engineering and Telecommunications, , Sydney, Australia College of Communications Engineering, Army Engineering University, Nanjing, China College of Automation Engineering, , Jiangning, Nanjing, China College of Automation Engineering, , Jiangning, Nanjing, ChinaA fault-detection method for relative navigation based on Kullback–Leibler divergence (KLD) is proposed. Different from the traditional χ 2 -based approaches, the KLD for a filter is following a hybrid distribution that combines χ 2 distribution and F -distribution. Using extended Kalman filter (EKF) as the estimator, the distance between the priori and posteriori data of EKF is calculated to detect the abnormal measurements. After fault detection step, a fault exclusion method is applied to remove the error observations from the fusion procedure. The proposed method is suitable for the Kalman filter-based multisensor relative navigation system. Simulation and experimental results show that the proposed method can detect the abnormal measurement successfully, and its positioning accuracy after fault detection and exclusion outperforms the traditional χ 2 -based method.https://doi.org/10.1177/1729881420979125 |
| spellingShingle | Jun Xiong Joon Wayn Cheong Zhi Xiong Andrew G Dempster Shiwei Tian Rong Wang Jianye Liu Fault-tolerant relative navigation based on Kullback–Leibler divergence International Journal of Advanced Robotic Systems |
| title | Fault-tolerant relative navigation based on Kullback–Leibler divergence |
| title_full | Fault-tolerant relative navigation based on Kullback–Leibler divergence |
| title_fullStr | Fault-tolerant relative navigation based on Kullback–Leibler divergence |
| title_full_unstemmed | Fault-tolerant relative navigation based on Kullback–Leibler divergence |
| title_short | Fault-tolerant relative navigation based on Kullback–Leibler divergence |
| title_sort | fault tolerant relative navigation based on kullback leibler divergence |
| url | https://doi.org/10.1177/1729881420979125 |
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