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地球卫星自主天文导航滤波方法性能分析 被引量:5

Analysis of filtering methods for satellite celestial navigation
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摘要 在系统硬件精度无法改进的条件下,滤波方法是影响地球卫星自主天文导航精度和实时性的最重要因素,本文针对地球卫星天文导航工程应用的需求,研究了目前导航系统中应用最为广泛的扩展卡尔曼滤波(EKF)、Unscented卡尔曼滤波(UKF)、Unscented粒子滤波(UPF)3种滤波方法,在滤波周期和噪声分布影响下的导航精度和实时性.半物理仿真结果表明,在相同仿真条件下,Unscented粒子滤波方法具有最高的导航精度,但计算量也最大,EKF方法计算量最小,导航精度最低.本文结果可为地球卫星自主导航系统中滤波方法的选择提供参考和依据. The filtering method becomes the most important factor affecting the navigation accuracy and timeconsumption,whenever the accuracy of sensors can not be improved anymore.In satellite navigation,the extended Kalman filter(EKF),unscented Kalman filter(UKF)and unscented particle filter(UPF)are the three widely used filtering methods.The performance of the system based on these three methods under different conditions is analyzed.Hardware-in-loop tests show that in the same condition,the UPF provides the highest navigation performance but requires the most computation;meanwhile the EKF gives the lowest navigation performance but needs the least computation.The conclusions drown by this study are useful in the design and analysis of autonomous navigation system of satellites.
作者 宁晓琳 马辛
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2010年第4期423-430,共8页 Control Theory & Applications
基金 国家自然科学基金资助项目(60874095) 国家"863"计划重大资助项目
关键词 地球卫星 天文导航 自主导航 滤波方法 earth satellites celestial navigation autonomous navigation filtering methods
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参考文献18

  • 1闵桂荣.空间技术的成就与发展趋势(上)[J].知识就是力量,1999,0(9):46-47. 被引量:1
  • 2闵桂荣.空间技术的成就与发展趋势(下)[J].知识就是力量,1999,0(10):46-47. 被引量:1
  • 3LONG A,LEUNG D,FOLTA D,et al.Autonomous navigation of high-earth satellites using celestial objects and doppler measure-ments[C] //AIAA Astrodynamis Speialist Conference.Denver:AIAA,2000:1-9.
  • 4NING X L,FANG J C.An autonomous celestial navigation method for LEO satellite based on unscented Kalman filter and information fusion[J].Aerospace Science and Technology,2007,11(2):222-228.
  • 5WHITE R L,GOUNLEY R B.Satellite autonomous navigation with SHAD[R].Cambridge,MA:The Charles Stark Draper Laboratory,1987.
  • 6FERGUSON J R.Autonomous navigation of USAF spacecraft[D].Austin:The University of Texas,1983.
  • 7齐国元,陈增强,袁著祉.非线性系统智能状态估计研究进展与展望[J].控制理论与应用,2003,20(6):813-818. 被引量:7
  • 8FARINA A,BENVENUTID.Tracking a ballistic target:comparison of several nonlinear filters[J].IEEE Transaction on Aerospace and Electronic Systems,2002,38(3):477-482.
  • 9房建成,张瑜,曾琪明.基于天体敏感器的自主导航技术[R].北京:北京航空航天大学,国防科学技术报告,2003.
  • 10JULIER S J,UHLMANN J K.A new extension of the Kalman filter to nonlinear systems[C] //Proceedings of the 11th International Symposium on Aerospace/Defense Sensing,Simulation and Controls.Orlando,Honda,USA:SPIE,1997.

二级参考文献137

  • 1王培德,史忠科,张友民,张洪才.非线性滤波与辨识的应用与发展[J].控制理论与应用,1993,10(2):121-128. 被引量:5
  • 2[1]ANDERSON B D O, MOORE J B. Optimal Filtering [ M]. Englewood Cliffs, NJ: Prentice-Hall, 1979.
  • 3[5]BATTIN R E. Astronautical guidance [M]. New York: McCrawHill, 1964:303 - 304.
  • 4[6]CARLSON N. A fast triangular factorization of square root filter[ J ]. The American Institute of Aeronautics and Astronautics ( AIAA), 1973, 11(9): 1259-1265.
  • 5[7]LJUNG L. Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems [ J]. IEEE Trans on Automatic Control, 1979,24(1):36- 50.
  • 6[8]BIERMAN G J. Measurement updating using the U-D factorization[ J ]. Automatica, 1976,12(3) :375 - 382.
  • 7[9]BIERMAN G J, THORNTON C L. Numerical comparison of Kalman filter algorithms: orbit determination case study [J]. Automatica, 1977, 13( 1 ) :23 - 35.
  • 8[10]OSHMAN Y. Gain-free square root information filter using the spectral decomposition [ J ]. J Guidance Control, and D Dynamics, 1989,12(5): 681-690.
  • 9[12]ZHOU D H, FRANK P M. Strong tracking filtering of nonlinear time-varying stochastic systems with colored noise: application to parameter estimation and empirical robustness analysis [ J ]. Int J Control, 1996,65(2) :295 - 307.
  • 10[13]CHAO C T, CHEN Y G, TENG C C. Simplification of fuzzy-neural systems using similarity analysis [ J]. IEEE Trans on Systems,Man, and Cybernetics-Part B: Cybernetics, 1996,26(2):344-354.

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