DocumentCode :
2580409
Title :
SINS/GPS/CNS information fusion system based on improved Huber filter with classified adaptive factors for high-speed UAVs
Author :
Wang, Rong ; Xiong, Zhi ; Liu, Jian-ye ; Li, Rongbing ; Peng, Hui
Author_Institution :
Navig. Res. Center, Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
fYear :
2012
fDate :
23-26 April 2012
Firstpage :
441
Lastpage :
446
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.
Keywords :
Gaussian processes; Global Positioning System; Kalman filters; autonomous aerial vehicles; inertial navigation; sensor fusion; CNS; GPS; Huber filter; Kalman filter; SINS; asynchronous measurement model; classified adaptive factors; high-speed UAV; information fusion system; integrated navigation system; nonGaussian characteristics; perturbed Gaussian mode; star sensor; system measurement noise feature; Adaptation models; Global Positioning System; Hafnium; Measurement uncertainty; Robustness; Silicon compounds; Dynamic errors; Huber robust filter; Inertial navigation; Integrated navigation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Position Location and Navigation Symposium (PLANS), 2012 IEEE/ION
Conference_Location :
Myrtle Beach, SC
ISSN :
2153-358X
Print_ISBN :
978-1-4673-0385-9
Type :
conf
DOI :
10.1109/PLANS.2012.6236913
Filename :
6236913
Link To Document :
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