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基于模糊交互式多模型算法跟踪临近空间目标

Tracking Near Space Target Based on Fuzzy Interacting Multiple Model Algorithm
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摘要 由于临近空间高超声速飞行器采用非弹道式机动飞行方式,飞行速度、高度、加速度不断变化,目标机动具有长周期机动特点,而且临近空间目标飞行速度快,具有较高的升阻比,且在大气层内长时间飞行,其运动轨迹往往呈现出"跳跃"特征,给地面防御系统对其定位和跟踪带来了巨大的困难,传统的滤波算法无法给出精确的目标状态估计,跟踪性能变差。为了更好满足非机动式弹道滤波的需要,通过模糊逻辑算法与交互式多模型算法相结合,形成模糊交互式多模型算法,实现对临近空间目标飞行器跟踪,并保证了定位跟踪精度在允许范围之内。Matlab仿真结果验证了算法的有效性。 As hypersonic vehicles in the near space often adopt the way of nonballistic maneuver flight with characteristics of high speed and lift-to-drag ratio, flying in atmosphere for a long time, whose motion trajectories are sometimes characterized by "hopping", their flight altitudes, flight velocities and flight accelerations are changing. Targets maneuver are characterized by long period maneuver, which has caused great difficulties for ground defense system to maneuver target localization and tracking. Tradition- al filtering algorithms obviously cannot give accurate target state estimation, tracking performance has de- clined. In order to better meet the needs of mobile trajectory filtering, a way of combining fuzzy logic al- gorithm and interacting multiple model algorithm (namely FIMM algorithm) is proposed for localization and tracking of near space target vehicle. This algorithm guarantees the accuracy of localization and tracking for target within the allowable range and validity of the algorithm is verified with Matlab simula- tion results.
作者 秦雷 李君龙
出处 《现代防御技术》 北大核心 2014年第5期108-114,126,共8页 Modern Defence Technology
关键词 模糊逻辑 交互式多模型 双站 临近空间 fuzzy logic interacting multiple model bi-station near space
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参考文献12

  • 1BLOM H A. P,BAR-SHALOM Y. The Interacting Mul- tiple Model Algorithm for Systems with a Jump-Linear Smoothing Application [ J]. IEEE Transactions on Auto- matic Control, 1988, 33 (8) :780 -783.
  • 2BAR-SHALOM Y, LI Xiao-rong. Estimation and Track- ing Principles, Techniques, and Software [ M ]. Bos- ton. MA: Artech House, 1993:461-465.
  • 3LI Xiao-rong. Design of an Interacting Multiple Model Algorithm for Air Traffic Control Tracking [ J ]. IEEE Transactions on Control Systems Technology, 1993, 1 (3) :186-194.
  • 4BAR-SHALOM Y, CHANG K C, BLOM H A P. Track- ing a Maneuvering Target Using Input Estimation Versus the Interacting Multiple Model Algorithm [ J ]. IEEE Transactions on Aerospace and Electronic Systems, 1989, AES (25): 296-300.
  • 5Um-Jik Lee, Young-Hoon Joo, Jin-Bae Park. Estima- ting Optimal Tracking Filter Performance for Manned Maneuvering Targets [ J]. International Journal of Con- trol, Automation, and Systems, 2003, 1 ( 1 ) : 93 -100.
  • 6CAMPO L, MOOKERJEE P, BAR-SHALOM Y. State Estimation for Systems with Sojourn-Time-Dependent Markov Model Switching [J]. IEEE Transaction on Au- tomatic Control, 1991, 36(2) :238-243.
  • 7TAKAGI T,SUGENO M. Fuzzy Identification of System and Its Applications to Modeling and Control [ J]. IEEE Transactions on Man and Cybernetics, 1985, SMC (15) :116-132.
  • 8MCGINNITY S, IRWIN G W. Fuzzy logic approach to maneuvering target tracking [ J]. IEE Proc-Radar, Sonar Navig. , 1998, 145(6) :337-341.
  • 9ZUO Dong-yang, HAN Chong-zhao, LIN Zheng, et al. Fuzzy Multiple Tracking Algorithm for Maneuvering Tar- get [J]. IEEE Transactions on Aerospace and Electron- ic Systems, 2002, AES (25) :296-300.
  • 10BAR-SHALOM Y, FORTMANN T E. Tracking and Da- ta Association [ M]. Beijing: Academic Press, 1988.

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