SINS/GPS/CNS Information Fusion System Based on Improved Huber Filter with Classified Adaptive Factors for High-speed UAVs

R. Wang, Z. Xiong, J-Y. Liu, R. Li, and H. 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.
Published in:	Proceedings of IEEE/ION PLANS 2012 April 24 - 26, 2012 Myrtle Beach Marriott Resort & Spa Myrtle Beach, South Carolina
Pages:	441 - 446
Cite this article:	Wang, R., Xiong, Z., Liu, J-Y., Li, R., Peng, H., "SINS/GPS/CNS Information Fusion System Based on Improved Huber Filter with Classified Adaptive Factors for High-speed UAVs," Proceedings of IEEE/ION PLANS 2012, Myrtle Beach, South Carolina , April 2012, pp. 441-446. https://doi.org/10.1109/PLANS.2012.6236913
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