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多传感器信息融合联邦滤波一般模型的理论与仿真研究 被引量:3

Theoretical and Simulation Study on General Model of Federated Filtering with Multi-sensor Information Fusion
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摘要 对多传感器信息融合联邦滤波一般理论模型及其实现方法进行了研究。结合应用需求分析了联邦滤波一般模型的特点,给出了实用的信息分配系数求取方法及该模型具体的算法实现途径。以惯性/卫星(GPS/北斗双星)/多普勒/星光(INS/GPS/RDSS/Doppler/CNS)飞行器组合导航系统为例进行了联邦滤波一般模型算法的仿真分析。仿真结果表明,所给出的一般模型实现算法,在保持该模型全局最优性的同时,具有数值计算稳定性好、计算量小、数据传输量小等优点,是一种改进型算法。 The general theoretical model and the way to put it into effect of federated filtering for multi-sensor information fusion are researched. For request of application, characteristics of general model are analyzed, the practical algorithm to get the info-partition coefficient and the specific method to realize the model are presented. Based on INS/GPS/RDSS/Doppler/CNS, a specialized integrated navigation system, math-simulating and analysis are proceeded. The results of simulation show that the way to realize general model which remain the global optimality, stability, high computational efficiency, is improved.
出处 《航空兵器》 2006年第4期7-10,共4页 Aero Weaponry
基金 国家863-702(2004AA721074)资助项目
关键词 多传感器 信息融合 联邦滤波 一般模型 multi-sensor information fusion federated filtering general model
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  • 1Magill D.T. Optimal Adaptive Estimation of Sampled Stochastic Processes. IEEE Trans. AC, 1965, 10 (5): 434-439.
  • 2Maybeck P S, Hentz K P. Investigation of Moving- Bank Multiple Model Adaptive Algorithms. J. Guidance, 1987,10 (1): 90-96.
  • 3Chaer W S, Bishop R H, Ghosh J. A Mixture -of- Experts Framework for Adaptive Kalman Filtering.IEEE Trans.SMC-Part B: Cybemetics, 1997, 27 (3): 452-464.
  • 4Alan S. Willsky, Edward Y. Chow, Stanley B. Getshwin, Christopher S. Greene, Paul K. Houpt, Andrew L.Kurkjian. Dynamic Model- Based Techniques for the Detection of Incidents on Freeways. IEEE Trans. AC, 1980,2.5 (3): 347- 359.
  • 5Carlson, N. A. Federated filter for computer- efficient, near- optimal GPS integration. Position Location and Navigation Symposium, 1996., W.F.F. 1996, 22 - 26 Apr 1996 Page (s) : 306 - 314.
  • 6任光,朱利民,于成,赵卫军.多模型卡尔曼滤波器的研究[J].大连海事大学学报,1999,25(4):1-5. 被引量:4
  • 7刘瑞华,刘建业.联邦滤波信息分配新方法[J].中国惯性技术学报,2001,9(2):28-32. 被引量:35

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  • 1刘勇,徐世杰.基于联邦UKF算法的月球探测器自主组合导航[J].宇航学报,2006,27(3):518-521. 被引量:17
  • 2穆荣军,崔乃刚.多传感器分层多级变结构组合导航信息融合方法[J].上海航天,2007,24(1):6-11. 被引量:2
  • 3邱恺,吴训忠,张宗麟,魏瑞轩.全局最优联邦滤波器信息分配原则[J].控制理论与应用,2007,24(1):39-45. 被引量:9
  • 4Zhang Y M, Ji Q. Active and dynamic information fusion for multisensor systems with dynamic Bayesian networks [J]. IEEE Trans on Systems, Man and Cybernetics, 2006, 36(2): 467-472.
  • 5Murphy K P. Dynamic Bayesian networks: Representation, inference and learning[D]. California University of California, 2002.
  • 6Zhang Y M. Active and dynamic information fusion with Bayesian networks[D]. Nevada: University of Nevada, 2004.
  • 7Shannon C E. A mathematical theory of communication [J]. Bell System Technical J, 1948, 27(10): 379-423; 623-656.
  • 8Kullback. Information theory and statistics[M]. New York: Wiley, 1959.
  • 9Jamshaid A, Fang J C. SINS/ANS/GPS integration using federated Kalman filter based on optimized information-sharing Coefficients[C]. AIAA. New York: NASA, 2005: 6028-6039.
  • 10Craig S S,,Seiler P.Estimation with lossy measure-ments:jump estimators for jump systems. IEEE Transactions on Automatic Control . 2003

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