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Constrained Robust Unscented Kalman Filter for BDS Navigation in Dense Urban Areas
Yin, Xiao1; Chai, Hongzhou1; Zhang, Yize2,3; Xiang, Minzhi1
2021-02-01
Source PublicationIEEE SENSORS JOURNAL
ISSN1530-437X
Volume21Issue:3Pages:3077-3086
AbstractIn dense urban environment, Multipath (MP) and Non-line-of-sight (NLOS) signals will degrade the performance of BeiDou Navigation Satellite System (BDS) Position, Velocity and Timing (PVT). In order to mitigate this negative impact, a Constrained Robust Unscented Kalman Filter (CRUKF) is implemented based on pseudorange/Doppler shift measurements. An equivalent weight function based on the innovation vector is constructed, which can overcome the problem of performance degrading of traditional robust methods caused by the inaccurate initial state vector. Then, the motion information, navigation direction and elevation, is included to further constrain the Robust UKF (RUKF) solution. The performance of CRUKF is analyzed using two real car tests in a dense building area, Tokyo. It is shown that there is a clear correlation between MP/NLOS errors and Position Dilution of Precision (PDOP), which seriously lows the positioning accuracy. Regarding the horizontal position, the Root Mean Square Error (RMSE) of CRUKF is 5.6 m, while those of Robust Iterative Least Square (RILS) and RUKF are 15.3 m and 6.4 m, respectively. Similar improvements are presented in vertical position and velocity and hence show the superior positioning performance of CRUKF. In addition, without sensor aiding or coupling, CRUKF can be suitable for real-time application of low-cost receiver.
KeywordBDS unscented Kalman filter robust motion constraint dense urban environment
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
DOI10.1109/JSEN.2020.3023104
Language英语
Funding ProjectNational Natural Science Foundation of China[41574010] ; National Natural Science Foundation of China[41604013]
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
WOS Research AreaEngineering ; Instruments & Instrumentation ; Physics
WOS SubjectEngineering, Electrical & Electronic ; Instruments & Instrumentation ; Physics, Applied
WOS IDWOS:000607394400060
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/79730
Collection中国科学院国家天文台
Corresponding AuthorYin, Xiao
Affiliation1.Informat Engn Univ, Sch Geospatial Informat, Zhengzhou 450001, Peoples R China
2.Tokyo Univ Marine Sci & Technol, Dept Maritime Syst Engn, Tokyo 1358533, Japan
3.Shanghai Astron Observ, Shanghai 200030, Peoples R China
Recommended Citation
GB/T 7714
Yin, Xiao,Chai, Hongzhou,Zhang, Yize,et al. Constrained Robust Unscented Kalman Filter for BDS Navigation in Dense Urban Areas[J]. IEEE SENSORS JOURNAL,2021,21(3):3077-3086.
APA Yin, Xiao,Chai, Hongzhou,Zhang, Yize,&Xiang, Minzhi.(2021).Constrained Robust Unscented Kalman Filter for BDS Navigation in Dense Urban Areas.IEEE SENSORS JOURNAL,21(3),3077-3086.
MLA Yin, Xiao,et al."Constrained Robust Unscented Kalman Filter for BDS Navigation in Dense Urban Areas".IEEE SENSORS JOURNAL 21.3(2021):3077-3086.
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