Data fusion for a GPS/INS tightly coupled positioning system with equality and inequality constraints using an aggregate constraint unscented Kalman filter

作     者：Yu, Hang Li, Zengke Wang, Jian Han, Houzeng 

作者机构：China Univ Min & Technol Sch Environm Sci & Spatial Informat Xuzhou Jiangsu Peoples R China Beijing Univ Civil Engn & Architecture Sch Geomat & Urban Spatial Informat Beijing Peoples R China 

出 版 物：《JOURNAL OF SPATIAL SCIENCE》 (区域科学杂志)

年 卷 期：2020年第65卷第3期

页      面：377-399页

核心收录：

学科分类：07[理学] 0705[理学-地理学] 0816[工学-测绘科学与技术] 070501[理学-自然地理学] 

基　　金：Fundamental Research Funds for the Central Universities [2015XKMS051] National Natural Science Foundation of China Natural Science Foundation of Jiangsu Province [BK20160247] 

主　　题：Aggregate constraint method unscented Kalman filter equality and inequality constraints GPS INS integrated system 

摘      要：It is well known that the unscented Kalman filter (UKF) has been successfully implemented for the integration of inertial and global positioning system (GPS) measurements. This paper proposes combining an aggregate constraint method with the UKF to solve the GPS/inertial navigation system (INS) integration with equality and inequality constraints. The proposed algorithm comprehensively combines the characteristics of the aggregate constraint method and the UKF, and achieves the results in a computationally efficient way. A numerical example shows the proposed algorithm avoids large computational expense and can achieve the same level of good applicability compared with the existing constrained Kalman filter.