Analysis of a robust Kalman filter in loosely coupled GPS/INS navigation system |
| |
| Affiliation: | 1. School of Automation, Harbin Engineering University, 145 Nantong Street, Harbin 150001, China;2. Science and Engineering Faculty, Queensland University of Technology, 2 George Street, Brisbane, QLD 4001, Australia;1. School of Automatics, Northwestern Polytechnical University, 710072 Xi?an, People?s Republic of China;2. School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Australia;1. School of Electronic and Information Engineering, Xi''an Jiaotong University, Xi''an 710049, People''s Republic of China;2. School of Software Engineering, Xi''an Jiaotong University, Xi''an 710049, People''s Republic of China;3. School of Communications and Information Engineering, Xi''an University of Posts and Telecommunications, Xi''an 710121, People''s Republic of China;1. NationalKey Laboratory for Electronic Measurement Technology, School of Instrumentation and Electronics, North University of China, Tai Yuan 030051, China;2. Schoolof Information and Communication Engineering, North University of China, Tai Yuan 030051, China |
| |
| Abstract: | GPS/INS integrated system is very subject to uncertainties due to exogenous disturbances, device damage, and inaccurate sensor noise statistics. Conventional Kalman filer has no robustness to address system uncertainties which may corrupt filter performance and even cause filter divergence. Based on the INS error dynamic equation, a robust Kalman filter is analyzed and applied in loosely coupled GPS/INS integration system. The norm bounded robust Kalman filter, with recursive form by solving two Riccati equations, guarantees a estimation variance bound for all the admissible uncertainties, and can evolve into the conventional Kalman filter if no uncertainties are considered. This paper will analyze the suitable case for the robust Kalman filter in GPS/INS system, the filter characteristics including parameter setting, parameter meaning, and filter convergence condition are discussed simutaneously. The robust filter performance will be compared with conventional Kalman filter through simulation results. |
| |
| Keywords: | GPS/INS Robust Kalman filter Riccati equation |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
