Electro-Optic Technology Application, Volume. 30, Issue 6, 60(2015)
State Dynamic Prediction Method Based on Beidou Navigator in Monitoring and Displaying
[1] [1] Welch G, Bishop G. An introduction to the kalman filer[J]. University of North Carolina at Chapel Hill: Technical Report, TR 95-041, 2004.
[2] [2] Julier S J, Uhlmann J K. Unscented filtering and nonlinear estimation[J]. Proceedings of the IEEE, 2004, 92(3):401-422.
[3] [3] DENG Xiao-long, XIE Jian-ying, GUO Wei-zhong. Bayesian target tracking based on particle filter[J]. Journal of Systems Engineering and Electronics, 2005, 16(3):545-549.
[4] [4] Fox D, Hightower J, Liao L, et al. Bayesian filtering for location estimation[J]. IEEE Pervasive Computing, 2003, 2(3):24-33.
[5] [5] Kalsson Rickard. Particle filtering for positioning and tracking applications [D]. Department of Electrical Engineering, Linkpings Universitet, 2005.
[6] [6] Rekleitis I M. A particle filter tutorial for mobile robot localization[J]. Montreal, Quebec, Canada: Centre for Intelligent Machines, McGill University, Technical Report: TM-CIM-04-02, 2004.
[7] [7] CHANG Cheng, Ansari Rashid. Kernel particle filter for visual tracking[J]. IEEE Signal Processing Letters, 2005, 12(3): 242-245.
[8] [8] Kwok C, Fox D, Meila M. Real-Time particle filters[J]. Proceedings of the IEEE, 2004, 92(3):469-484.
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ZHAO Xiu-ying, XIONG Zhuang, XIAO Jing-xin, XU Wen. State Dynamic Prediction Method Based on Beidou Navigator in Monitoring and Displaying[J]. Electro-Optic Technology Application, 2015, 30(6): 60
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Received: Oct. 19, 2015
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Published Online: Jan. 20, 2016
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