{"title":"基于超宽带和惯性神经网络的鲁棒室内车辆定位策略","authors":"Long Cheng;Chen Cui;Hao Zhang","doi":"10.1109/TVT.2025.3527008","DOIUrl":null,"url":null,"abstract":"High-precision indoor vehicle localization technology has recently been a research hotspot for indoor location services. This paper investigate the indoor combined positioning technology based on Ultra wide band (UWB) and inertial navigation system(INS), aiming to overcome the limitations of UWB in non-line of sight (NLOS) environment and cumulative errors of INS. For dealing with NLOS errors conveniently, we propose a two-layer NLOS error weakening method. Firstly, k-mediods clustering method is used to preprocess the obtained distance measurements, and some of the measurements containing NLOS errors are replaced with the measurements undisturbed by NLOS transmission. The processed result is processed again with gray Kalman filter, which reduces the process noise and NLOS error. A hybrid Gaussian fitting approach is suggested to determine the propagation conditions and simulate the likelihood of propagation through the residual after calculating the difference between the distance that was filtered and the distance that was measured. The two-sided correction technique changed the findings of the fitting method and the improved particle filtering method. The adaptive Kalman filter was then used to combine the INS and UWB location results to get the final location data. Simulation and experimental results show that the proposed algorithm owns higher localization accuracy and dependability.","PeriodicalId":13421,"journal":{"name":"IEEE Transactions on Vehicular Technology","volume":"74 5","pages":"7292-7302"},"PeriodicalIF":7.1000,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Robust Indoor Vehicle Localization Strategy Based on UWB and INS\",\"authors\":\"Long Cheng;Chen Cui;Hao Zhang\",\"doi\":\"10.1109/TVT.2025.3527008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-precision indoor vehicle localization technology has recently been a research hotspot for indoor location services. This paper investigate the indoor combined positioning technology based on Ultra wide band (UWB) and inertial navigation system(INS), aiming to overcome the limitations of UWB in non-line of sight (NLOS) environment and cumulative errors of INS. For dealing with NLOS errors conveniently, we propose a two-layer NLOS error weakening method. Firstly, k-mediods clustering method is used to preprocess the obtained distance measurements, and some of the measurements containing NLOS errors are replaced with the measurements undisturbed by NLOS transmission. The processed result is processed again with gray Kalman filter, which reduces the process noise and NLOS error. A hybrid Gaussian fitting approach is suggested to determine the propagation conditions and simulate the likelihood of propagation through the residual after calculating the difference between the distance that was filtered and the distance that was measured. The two-sided correction technique changed the findings of the fitting method and the improved particle filtering method. The adaptive Kalman filter was then used to combine the INS and UWB location results to get the final location data. Simulation and experimental results show that the proposed algorithm owns higher localization accuracy and dependability.\",\"PeriodicalId\":13421,\"journal\":{\"name\":\"IEEE Transactions on Vehicular Technology\",\"volume\":\"74 5\",\"pages\":\"7292-7302\"},\"PeriodicalIF\":7.1000,\"publicationDate\":\"2025-01-08\",\"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/10833661/\",\"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/10833661/","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}
A Robust Indoor Vehicle Localization Strategy Based on UWB and INS
High-precision indoor vehicle localization technology has recently been a research hotspot for indoor location services. This paper investigate the indoor combined positioning technology based on Ultra wide band (UWB) and inertial navigation system(INS), aiming to overcome the limitations of UWB in non-line of sight (NLOS) environment and cumulative errors of INS. For dealing with NLOS errors conveniently, we propose a two-layer NLOS error weakening method. Firstly, k-mediods clustering method is used to preprocess the obtained distance measurements, and some of the measurements containing NLOS errors are replaced with the measurements undisturbed by NLOS transmission. The processed result is processed again with gray Kalman filter, which reduces the process noise and NLOS error. A hybrid Gaussian fitting approach is suggested to determine the propagation conditions and simulate the likelihood of propagation through the residual after calculating the difference between the distance that was filtered and the distance that was measured. The two-sided correction technique changed the findings of the fitting method and the improved particle filtering method. The adaptive Kalman filter was then used to combine the INS and UWB location results to get the final location data. Simulation and experimental results show that the proposed algorithm owns higher localization accuracy and dependability.
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.