The Application of Kalman Filter on the Initial Alignment Algorithm of Strapdown Navigation System on Stationary Base
Initial alignment is the process whereby the orientation of the axes of an inertial navigation system is determined with respect to the reference system. In this paper, the initial alignment error equations of the strapdown inertial navigation system (SINS) have been presented and discussed. The observability of SINS error models are discussed, and then a reduced order Kalman filter with five states and a full order Kalman filter with eight states are designed respectively to estimate the states of error models. It is shown that not all of these states are observable, and those states which are observable are different in rate of convergence. Results of the simulation show that the reduced order Kalman filter can guarantee higher accuracy and has less calculating burden compared with the full order Kalman filter.
Strapdown Inertial Navigation System (SINS) Kalman Filter Initial Alignment Observability
Youlong Wu Jinling Wang Xiaoming Wang Peng Cao
School of Surveying and Spatial Information Systems, University of New South Wales, Sydney 2052, Aus School of Mechanical Engineer, Nanjing University of Science and Technology, Nanjing 210094, China
国际会议
南京
英文
358-363
2012-08-16（万方平台首次上网日期，不代表论文的发表时间）