{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T20:30:33Z","timestamp":1781037033673,"version":"3.54.1"},"reference-count":40,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T00:00:00Z","timestamp":1692662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Transfer of Ownership of Patent Package for Offshore Engineering Technology and Operation and Maintenance Intelligent System and the MNR Key Laboratory of Eco-Environmental Science and Technology","award":["MEEST-2021-02"],"award-info":[{"award-number":["MEEST-2021-02"]}]},{"name":"Transfer of Ownership of Patent Package for Offshore Engineering Technology and Operation and Maintenance Intelligent System and the MNR Key Laboratory of Eco-Environmental Science and Technology","award":["ZR2022MD03"],"award-info":[{"award-number":["ZR2022MD03"]}]},{"name":"Research on key technologies of cooperative navigation and positioning of underwater AUV formation based on the BeiDou inertial navigation underwater acoustic combination","award":["MEEST-2021-02"],"award-info":[{"award-number":["MEEST-2021-02"]}]},{"name":"Research on key technologies of cooperative navigation and positioning of underwater AUV formation based on the BeiDou inertial navigation underwater acoustic combination","award":["ZR2022MD03"],"award-info":[{"award-number":["ZR2022MD03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global Navigation Satellite Systems (GNSS) integrated with Inertial Navigation Systems (INS) have been widely applied in many Intelligent Transport Systems. However, due to the influence of various factors, such as complex urban environments, etc., accurately describing the measurement noise statistics of GNSS receivers and inertial sensors is difficult. An inaccurate definition of the measurement noise covariance matrix will lead to the rapid divergence of the position error of the integrated navigation system. To overcome this problem, this paper proposed a Robust Adaptive Extended Kalman Filter (RAKF) method based on an improved measurement noise covariance matrix. By analyzing and considering the position accuracy factors, measurement factor, and position standard deviation in GNSS measurement results, this paper constructed the optimal measurement noise covariance matrix. Based on the Huber model, this paper constructed a two-stage robust adaptive factor expression and obtained the robust adaptive factors with and without abnormal disturbances. And robust adaptive filtering was carried out. To assess the performance of this method, the author conducted experiments on land vehicles by using a self-developed POS system (GNSS\/INS combined navigation system). The classic Extended Kalman Filter algorithm (EKF), Adaptive Kalman Filter (AKF) algorithm, Robust Kalman Filter (RKF) algorithm, and the proposed method were compared through data processing. Experimental results show that compared with the classical EKF, AKF, and RKF, the positioning accuracies of the proposed method were improved by 72.43%, 2.54%, and 47.82%, respectively, in the vehicle land experiment. In order to further evaluate the performance of this method, the vehicle data were subjected to different times and degrees of disturbance experiments. Experimental results show that compared with EKF, AKF, and RKF, the heading angle accuracy had obvious advantages, and its accuracy was improved by 34.65%, 31.53%, and 18.36%, respectively. Therefore, this method can effectively monitor and isolate disturbance and improve the robustness, reliability, accuracy, and stability of GNSS\/INS integrated navigation systems in complex urban environments.<\/jats:p>","DOI":"10.3390\/rs15174125","type":"journal-article","created":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T08:01:21Z","timestamp":1692777681000},"page":"4125","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["A Robust Adaptive Extended Kalman Filter Based on an Improved Measurement Noise Covariance Matrix for the Monitoring and Isolation of Abnormal Disturbances in GNSS\/INS Vehicle Navigation"],"prefix":"10.3390","volume":"15","author":[{"given":"Zhihui","family":"Yin","sequence":"first","affiliation":[{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jichao","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1241-8650","authenticated-orcid":false,"given":"Yue","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"},{"name":"College of Electronic Information, Wuhan University, Wuhan 430072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengli","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"},{"name":"Key Laboratory of Ocean Geomatics, Ministry of Natural Resources, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dashuai","family":"Chai","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-informatics, Shandong Jianzhu University, Jinan 250101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haonan","family":"Cui","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,22]]},"reference":[{"key":"ref_1","first-page":"1006","article-title":"PNT intelligent services","volume":"50","author":"Yang","year":"2021","journal-title":"Acta Geod. 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