Research on Information Intermittent Fusion of ASPN System in the Long-endurance UAVs

Jian-xin Xu, Zhi Xiong, Jian-ye Liu, Xue-bo Kong, Song Han

Abstract:	In the long-endurance UAVs, the conventional INS/GNSS integrated navigation system is widespread used. But with the increasing man-made interference and electromagnetic environment worsening, the GNSS system will be easily failing in location. In that case, using other aided navigation systems based on the characteristics of objects & geophysical field is necessary. However, the aided navigation systems such as celestial navigation, scene matching navigation and terrain aided navigation cannot work continuously during the long time flight. This will cause wrong detection by the traditional method. So a scheme of seamless navigation based on the characteristics of objects & geophysical field and an improved algorithm of residual chi-square fault detection are proposed in this paper. The simulation results show that the designed method can effectively solve the problem of wrong detection, and ensure the seamless navigation system works properly during the flight mission. The Navigation Research Center (NRC) of Nanjing University of Aeronautics and Astronautics (http://www.nuaanrc.com) is engaged in the research of navigation technology, and has done a series of research on all source information fusion. Up to now, a great deal of achievement has been made in the following fields: Strap-down Inertial Navigation System, Inertial Integrated Navigation System, Global Satellite Positioning System, Terrain Aided Navigation System, Fault-Tolerant Technique of Multi Inertial Navigation Subsystem, Modern Optimization Filtering Theory, Precision Measurement System and so on. This paper is part of the NRC research achievement.
Published in:	Proceedings of IEEE/ION PLANS 2016 April 11 - 14, 2016 Hyatt Regency Hotel Savannah, GA
Pages:	507 - 513
Cite this article:	Xu, Jian-xin, Xiong, Zhi, Liu, Jian-ye, Kong, Xue-bo, Han, Song, "Research on Information Intermittent Fusion of ASPN System in the Long-endurance UAVs," Proceedings of IEEE/ION PLANS 2016, Savannah, GA, April 2016, pp. 507-513.
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