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Proceedings Paper

Application of the least square filtering in initial alignment of SINS
Author(s): Long Zhao; Li Wang
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Paper Abstract

When the statistics of the system noise and the observation noise are unknown, or almost unknown, the state estimation error computed by Kalman Filtering will be much bigger, or the Kalman Filter may become divergence. In order to avoid this demerit, a Least Square Filtering is presented. It weighs the observation data adaptively only without the requirement of the statistics of the noise. This algorithm is used to Strapdown Inertial Navigation System (SINS) initial alignment and compared with the Kalman Filtering. The simulation results show that the Least Square (LS) Filtering has faster convergent speed than the Kalman Filtering.

Paper Details

Date Published: 13 October 2008
PDF: 5 pages
Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 712816 (13 October 2008); doi: 10.1117/12.806646
Show Author Affiliations
Long Zhao, Beihang Univ. (China)
Li Wang, Beihang Univ. (China)


Published in SPIE Proceedings Vol. 7128:
Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment

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