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Mathematical Problems in Engineering - Volume 2014 2014, Article ID 609154, 12 pages -

Research ArticleSchool of Instrument Science and Optoelectronics Engineering, Beihang University, Beijing 100191, China

Received 30 June 2014; Revised 24 September 2014; Accepted 24 September 2014; Published 16 October 2014

Academic Editor: Jian Guo Zhou

Copyright © 2014 Xueyun Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Among all integration levels currently available for Global Positioning System GPS and Inertial Navigation System INS Integrated System, ultra-tightly coupled UTC GPS-INS system is the best choice for accurate and reliable navigation. Nevertheless the performance of UTC GPS-INS system degrades in challenging environments, such as jamming, changing noise of GPS signals, and high dynamic maneuvers. When low-end Inertial Measurement Units IMUs based on MEMS sensors are employed, the performance degradation will be more severe. To solve this problem, a reinforced UTC GPS-INS system is proposed. Two techniques are adopted to deal with jamming and high dynamics. Firstly, adaptive integration Kalman filter IKF based on fuzzy logics is developed to reinforce the antijamming ability. The parameters of membership functions MFs are adjusted and optimized through self-developed neutral network. Secondly, a Doppler frequency error estimator based on Kalman filter is designed to improve the navigation performance under high dynamics. A complete simulation platform is established to evaluate the reinforced system. Results demonstrate that the proposed system architecture significantly improves navigation performance in challenging environments and it is a more advanced solution to accurate and reliable navigation than traditional UTC GPS-INS system.

Autor: Xueyun Wang, Kui Li, Pengyu Gao, and Wei Wang



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