NDLI: SINS/GPS/CNS information fusion system based on improved Huber filter with classified adaptive factors for high-speed UAVs

Content Provider	IEEE Xplore Digital Library
Author	Rong Wang Zhi Xiong Jian-ye Liu Rongbing Li Hui Peng
Copyright Year	2012
Description	Author affiliation: Navigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Jiangsu, 210016, China (Rong Wang; Zhi Xiong; Jian-ye Liu; Rongbing Li; Hui Peng)
Abstract	For High-speed UAV, the measurement noise of GPS and star sensor show non-Gaussian characteristics in high-dynamic and high speed flight. In order to improve the system performance in the above situation, this paper presents an INS/GPS/CNS integrated navigation system and builds the asynchronous measurement model. The system measurement noise feature has also been analyzed according to a perturbed Gaussian mode. Furthermore, this paper designs an integrated navigation algorithm based on improved Huber filter with classified adaptive factors (CAHF), which could improve the precision of position, velocity and attitude in the condition of perturbed measurement noise. Simulation cases involving both CAHF and Kalman Filter are provided to validate the advantage of CAHF.
Starting Page	441
Ending Page	446
File Size	1079445
Page Count	6
File Format	PDF
ISBN	9781467303859
ISSN	21533598
e-ISBN	9781467303873
DOI	10.1109/PLANS.2012.6236913
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Global Positioning System Silicon compounds Hafnium Robustness Measurement uncertainty Adaptation models Huber robust filter Integrated navigation Inertial navigation Dynamic errors
Content Type	Text
Resource Type	Article

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