Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems
Fault detection is crucial to ensure the reliability of localization systems. However, conventional fault detection methods usually assume that noises in the system have a Gaussian distribution, limiting their effectiveness in real-world applications. This study proposes a fault detection algorithm...
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Institute of Navigation
2025-02-01
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| Series: | Navigation |
| Online Access: | https://navi.ion.org/content/72/1/navi.684 |
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| _version_ | 1850161412110811136 |
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| author | Penggao Yan Zhengdao Li Feng Huang Weisong Wen Li-Ta Hsu |
| author_facet | Penggao Yan Zhengdao Li Feng Huang Weisong Wen Li-Ta Hsu |
| author_sort | Penggao Yan |
| collection | DOAJ |
| description | Fault detection is crucial to ensure the reliability of localization systems. However, conventional fault detection methods usually assume that noises in the system have a Gaussian distribution, limiting their effectiveness in real-world applications. This study proposes a fault detection algorithm for an extended Kalman filter (EKF)-based localization system by modeling non-Gaussian noises as a Gaussian mixture model (GMM). The relationship between GMM-distributed noises and the measurement residual is rigorously established through error propagation, which is utilized to construct the test statistic for a chi-squared test. The proposed method is applied to an EKF-based two-dimensional light detection and ranging/inertial measurement unit integrated localization system. Experimental results in a simulated urban environment show that the proposed method exhibits a 30% improvement in the detection rate and a 17%–23% reduction in the detection delay, compared with the conventional method with Gaussian noise modeling. |
| format | Article |
| id | doaj-art-83d64121ba044a1785749dcfec30e869 |
| institution | OA Journals |
| issn | 2161-4296 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Institute of Navigation |
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| series | Navigation |
| spelling | doaj-art-83d64121ba044a1785749dcfec30e8692025-08-20T02:22:50ZengInstitute of NavigationNavigation2161-42962025-02-0172110.33012/navi.684navi.684Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization SystemsPenggao YanZhengdao LiFeng HuangWeisong WenLi-Ta HsuFault detection is crucial to ensure the reliability of localization systems. However, conventional fault detection methods usually assume that noises in the system have a Gaussian distribution, limiting their effectiveness in real-world applications. This study proposes a fault detection algorithm for an extended Kalman filter (EKF)-based localization system by modeling non-Gaussian noises as a Gaussian mixture model (GMM). The relationship between GMM-distributed noises and the measurement residual is rigorously established through error propagation, which is utilized to construct the test statistic for a chi-squared test. The proposed method is applied to an EKF-based two-dimensional light detection and ranging/inertial measurement unit integrated localization system. Experimental results in a simulated urban environment show that the proposed method exhibits a 30% improvement in the detection rate and a 17%–23% reduction in the detection delay, compared with the conventional method with Gaussian noise modeling.https://navi.ion.org/content/72/1/navi.684 |
| spellingShingle | Penggao Yan Zhengdao Li Feng Huang Weisong Wen Li-Ta Hsu Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems Navigation |
| title | Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems |
| title_full | Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems |
| title_fullStr | Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems |
| title_full_unstemmed | Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems |
| title_short | Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems |
| title_sort | fault detection algorithm for gaussian mixture noises an application in lidar imu integrated localization systems |
| url | https://navi.ion.org/content/72/1/navi.684 |
| work_keys_str_mv | AT penggaoyan faultdetectionalgorithmforgaussianmixturenoisesanapplicationinlidarimuintegratedlocalizationsystems AT zhengdaoli faultdetectionalgorithmforgaussianmixturenoisesanapplicationinlidarimuintegratedlocalizationsystems AT fenghuang faultdetectionalgorithmforgaussianmixturenoisesanapplicationinlidarimuintegratedlocalizationsystems AT weisongwen faultdetectionalgorithmforgaussianmixturenoisesanapplicationinlidarimuintegratedlocalizationsystems AT litahsu faultdetectionalgorithmforgaussianmixturenoisesanapplicationinlidarimuintegratedlocalizationsystems |