Integrity for Belief Propagation-Based Cooperative Positioning

被引:0
作者
Xiong, Jun [1 ]
Xiong, Zhi [2 ]
Xie, Xiangpeng [1 ]
Zhuang, Yuan [3 ]
Zheng, Yu [4 ]
Xiong, Shixun [1 ]
Cheong, Joon Wayn [5 ]
Dempster, Andrew G. [5 ]
机构
[1] Nanjing Univ Posts & Telecommun, Sch Internet Things, Nanjing 210003, Jiangsu, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Automat, Nanjing 210016, Jiangsu, Peoples R China
[3] Wuhan Univ, LIESMARS, Wuhan 430072, Peoples R China
[4] China North Ind Grp Corp, Nav & Control Technol Res Inst, Beijing 100821, Peoples R China
[5] Univ New South Wales, Sch Elect Elect & Telecommun Engn, Sydney, NSW 2052, Australia
基金
中国国家自然科学基金;
关键词
Monitoring; Global navigation satellite system; Sensors; Receivers; Estimation; Probability density function; Distance measurement; Cooperative positioning; integrity monitoring; belief propagation; error bound; protection level; FAULT-DETECTION; LOCALIZATION; FUSION; RAIM;
D O I
10.1109/TITS.2024.3361678
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A belief propagation (BP) based cooperative integrity monitoring (BP-CIM) algorithm is proposed in this work. BP is widely adopted as the cooperative positioning (CP) estimator, however, the corresponding integrity problem is not solved which restricts its practical application. To guarantee the reliability of a BP-based CP system, our proposed BP-CIM can detect the faulty observations in a distributed approach. Meanwhile, error analysis for BP is performed to derive the CP estimation error bound, which is subsequently used to determine the protection level (PL) of BP-CIM. The simulation and experimental results show that BP-CIM outperforms many existing fault-tolerant CP algorithms in the sides of accuracy and robustness, and the calculated PL can provide a conservative error bound for the estimated CP states. BP-CIM framework can be further extended to many other multi-sensor CP systems to improve the system reliability.
引用
收藏
页码:11345 / 11358
页数:14
相关论文
共 42 条
[1]   Multi-sensor fusion approach with fault detection and exclusion based on the Kullback-Leibler Divergence: Application on collaborative multi-robot system [J].
Al Hage, Joelle ;
El Najjar, Maan E. ;
Pomorski, Denis .
INFORMATION FUSION, 2017, 37 :61-76
[2]   A DSRC Doppler-Based Cooperative Positioning Enhancement for Vehicular Networks With GPS Availability [J].
Alam, Nima ;
Balaei, Asghar Tabatabaei ;
Dempster, Andrew G. .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2011, 60 (09) :4462-4470
[3]   Cooperative Position Prediction: Beyond Vehicle-to-Vehicle Relative Positioning [J].
Ansari, Keyvan .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 21 (03) :1121-1130
[4]   Kalman Filter-Based RAIM for GNSS Receivers [J].
Bhattacharyya, Susmita ;
Gebre-Egziabher, Demoz .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2015, 51 (03) :2444-2459
[5]  
Davison J., 2019, ARXIV
[6]  
Eustice RM, 2005, IEEE INT CONF ROBOT, P2417
[7]  
Falletti E., 2011, Handbook of Position Location: Theory, Practice, and Advances, P709
[8]  
Gabela J., 2021, THESIS U MELBOURNE M
[9]  
Grover Brown R., 1997, Navigation. Journal of the Institute of Navigation, V44, P425
[10]   GNSS receiver autonomous integrity monitoring (RAIM) performance analysis [J].
Hewitson, Steve ;
Wang, Jinling .
GPS SOLUTIONS, 2006, 10 (03) :155-170