{"title":"SINS/GNSS紧密耦合车载组合导航左/右不变李群误差","authors":"Maosong Wang;Jiarui Cui;Wenqi Wu","doi":"10.1109/TVT.2025.3542441","DOIUrl":null,"url":null,"abstract":"Tightly coupled strapdown inertial navigation system (SINS)/global navigation satellite system (GNSS) integrated navigation, which utilizes GNSS pseudo-range and pseudo-range rate measurements for state estimation in vehicular navigation systems, demonstrates enhanced reliability and accuracy in challenging GNSS environments. While the extended Kalman filter (EKF) remains the predominant nonlinear algorithm in SINS/GNSS integration, it suffers from performance degradation due to covariance inconsistency issues. To address this limitation, this paper proposes a novel nonlinear state error-based Lie group extended Kalman filter (LG-EKF) for tightly coupled SINS/GNSS integrated navigation. The study first presents a tutorial example illustrating the necessity of transformed nonlinear state error and then provides detailed derivations of LG-EKF equations using both right invariant error (LG-EKF-R) and left invariant error (LG-EKF-L). Through Monte Carlo simulations and uncrewed aerial vehicle (UAV) field tests, the research demonstrates the performance differences in system dynamics between LG-EKF-R and LG-EKF-L. The results indicate that LG-EKF-R, operating at a lower propagation rate, achieves comparable accuracy to LG-EKF-L with a higher propagation rate, offering a more efficient solution for integrated navigation systems.","PeriodicalId":13421,"journal":{"name":"IEEE Transactions on Vehicular Technology","volume":"74 6","pages":"8975-8988"},"PeriodicalIF":7.1000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Left/Right Invariant Lie Group Error for SINS/GNSS Tightly Coupled Vehicular Integrated Navigation\",\"authors\":\"Maosong Wang;Jiarui Cui;Wenqi Wu\",\"doi\":\"10.1109/TVT.2025.3542441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tightly coupled strapdown inertial navigation system (SINS)/global navigation satellite system (GNSS) integrated navigation, which utilizes GNSS pseudo-range and pseudo-range rate measurements for state estimation in vehicular navigation systems, demonstrates enhanced reliability and accuracy in challenging GNSS environments. While the extended Kalman filter (EKF) remains the predominant nonlinear algorithm in SINS/GNSS integration, it suffers from performance degradation due to covariance inconsistency issues. To address this limitation, this paper proposes a novel nonlinear state error-based Lie group extended Kalman filter (LG-EKF) for tightly coupled SINS/GNSS integrated navigation. The study first presents a tutorial example illustrating the necessity of transformed nonlinear state error and then provides detailed derivations of LG-EKF equations using both right invariant error (LG-EKF-R) and left invariant error (LG-EKF-L). Through Monte Carlo simulations and uncrewed aerial vehicle (UAV) field tests, the research demonstrates the performance differences in system dynamics between LG-EKF-R and LG-EKF-L. The results indicate that LG-EKF-R, operating at a lower propagation rate, achieves comparable accuracy to LG-EKF-L with a higher propagation rate, offering a more efficient solution for integrated navigation systems.\",\"PeriodicalId\":13421,\"journal\":{\"name\":\"IEEE Transactions on Vehicular Technology\",\"volume\":\"74 6\",\"pages\":\"8975-8988\"},\"PeriodicalIF\":7.1000,\"publicationDate\":\"2025-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Vehicular Technology\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10904024/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Vehicular Technology","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10904024/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Left/Right Invariant Lie Group Error for SINS/GNSS Tightly Coupled Vehicular Integrated Navigation
Tightly coupled strapdown inertial navigation system (SINS)/global navigation satellite system (GNSS) integrated navigation, which utilizes GNSS pseudo-range and pseudo-range rate measurements for state estimation in vehicular navigation systems, demonstrates enhanced reliability and accuracy in challenging GNSS environments. While the extended Kalman filter (EKF) remains the predominant nonlinear algorithm in SINS/GNSS integration, it suffers from performance degradation due to covariance inconsistency issues. To address this limitation, this paper proposes a novel nonlinear state error-based Lie group extended Kalman filter (LG-EKF) for tightly coupled SINS/GNSS integrated navigation. The study first presents a tutorial example illustrating the necessity of transformed nonlinear state error and then provides detailed derivations of LG-EKF equations using both right invariant error (LG-EKF-R) and left invariant error (LG-EKF-L). Through Monte Carlo simulations and uncrewed aerial vehicle (UAV) field tests, the research demonstrates the performance differences in system dynamics between LG-EKF-R and LG-EKF-L. The results indicate that LG-EKF-R, operating at a lower propagation rate, achieves comparable accuracy to LG-EKF-L with a higher propagation rate, offering a more efficient solution for integrated navigation systems.
期刊介绍:
The scope of the Transactions is threefold (which was approved by the IEEE Periodicals Committee in 1967) and is published on the journal website as follows: Communications: The use of mobile radio on land, sea, and air, including cellular radio, two-way radio, and one-way radio, with applications to dispatch and control vehicles, mobile radiotelephone, radio paging, and status monitoring and reporting. Related areas include spectrum usage, component radio equipment such as cavities and antennas, compute control for radio systems, digital modulation and transmission techniques, mobile radio circuit design, radio propagation for vehicular communications, effects of ignition noise and radio frequency interference, and consideration of the vehicle as part of the radio operating environment. Transportation Systems: The use of electronic technology for the control of ground transportation systems including, but not limited to, traffic aid systems; traffic control systems; automatic vehicle identification, location, and monitoring systems; automated transport systems, with single and multiple vehicle control; and moving walkways or people-movers. Vehicular Electronics: The use of electronic or electrical components and systems for control, propulsion, or auxiliary functions, including but not limited to, electronic controls for engineer, drive train, convenience, safety, and other vehicle systems; sensors, actuators, and microprocessors for onboard use; electronic fuel control systems; vehicle electrical components and systems collision avoidance systems; electromagnetic compatibility in the vehicle environment; and electric vehicles and controls.