FEMASF: An SVD-Based Algorithm for Accurately Estimating the Mounting Angle and Scale Factor

doi:10.1109/TITS.2025.3543255

	FEMASF: An SVD-Based Algorithm for Accurately Estimating the Mounting Angle and Scale Factor
	Ning, Bokun 1; Luo, Haiyong 2; Bao, Linfeng 3; Zhao, Fang 1; Wu, Fan 1
	2025-04-01
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
ISSN	1524-9050
卷号	26 期号:4 页码:4504-4516
摘要	Accurately estimating the position and attitude of vehicles is essential for intelligent transportation systems. The GNSS/INS integrated system offers precise navigation information. However, the system's positioning errors may accumulate rapidly in challenging GNSS signal conditions. Odometer (ODO) and nonholonomic constraints (NHC) are commonly employed to mitigate the rapid accumulation of INS errors. Compensating for the mounting angles of INS and the scale factor of the odometer is necessary to fully exploit the potential of ODO/NHC. However, many studies employ Kalman filters with small mounting angle assumption, which limits their applicability for large mounting angles in practice. To accurately estimate the mounting angle of INS with any installation attitude, we propose a new algorithm called Fast Estimation of Mounting Angle and Scale Factor (FEMASF). FEMASF employs Singular Value Decomposition (SVD) to obtain a closed-form solution for the parameters. It also incorporates an enhanced Sage-Husa scheme, enhancing overall estimation accuracy by reducing the weight of outlier data through a forgetting factor. Extensive simulation experimental results demonstrate that our proposed FEMASF algorithm outperforms filter-based methods in terms of accuracy and convergence speed for large mounting angles. Specifically, for the -90 degrees mounting angle, FEMASF achieves 0.45 degrees angle error, while the velocity-based Kalman filter (VKF) fails to converge and the position-based Kalman filter (PKF) yields about 4 degrees error. Furthermore, neither VKF nor PKF converges for the 120 degrees mounting angle, whereas FEMASF exhibits only about 3.2 degrees estimation error.
关键词	Estimation Accuracy Parameter estimation Convergence Odometers Heuristic algorithms Navigation Global navigation satellite system Kalman filters Closed-form solutions GNSS/INS positioning ODO/NHC IMU mounting angle odometer scale factor singular value decomposition(SVD) Sage-Husa
DOI	10.1109/TITS.2025.3543255
收录类别	SCI
语种	英语
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences[XDA28040500] ; National Natural Science Foundation of China[62261042] ; Key Research Projects of the Joint Research Fund for Beijing Natural Science Foundation ; Fengtai Rail Transit Frontier Research Joint Fund[L221003]
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:001456404200014
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/40601
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Luo, Haiyong; Zhao, Fang
作者单位	1.Beijing Univ Posts & Telecommun, Sch Software Engn, Beijing 100876, Peoples R China 2.Chinese Acad Sci, Beijing Key Lab Mobile Comp & Pervas Device, Inst Comp Technol, Beijing 100190, Peoples R China 3.SZ Da Jiang Innovat DJI Sci & Technol Co Ltd, Shenzhen 518057, Peoples R China
推荐引用方式 GB/T 7714	Ning, Bokun,Luo, Haiyong,Bao, Linfeng,et al. FEMASF: An SVD-Based Algorithm for Accurately Estimating the Mounting Angle and Scale Factor[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2025,26(4):4504-4516.
APA	Ning, Bokun,Luo, Haiyong,Bao, Linfeng,Zhao, Fang,&Wu, Fan.(2025).FEMASF: An SVD-Based Algorithm for Accurately Estimating the Mounting Angle and Scale Factor.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,26(4),4504-4516.
MLA	Ning, Bokun,et al."FEMASF: An SVD-Based Algorithm for Accurately Estimating the Mounting Angle and Scale Factor".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 26.4(2025):4504-4516.