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Volume 40 Issue 5
May  2014
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Journal of Beijing University of Aeronautics and Astronautics  > 2014  >  40(5): 651-657.
Zhou Zheng, Liu Jinmang, Guo Xiangkeet al. Adaptive tracking algorithm for reentry vehicle based on stochastic model approximation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(5): 651-657. doi: 10.13700/j.bh.1001-5965.2013.0359(in Chinese)
Citation: Zhou Zheng, Liu Jinmang, Guo Xiangkeet al. Adaptive tracking algorithm for reentry vehicle based on stochastic model approximation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(5): 651-657. doi: 10.13700/j.bh.1001-5965.2013.0359(in Chinese)
shu

Adaptive tracking algorithm for reentry vehicle based on stochastic model approximation

doi: 10.13700/j.bh.1001-5965.2013.0359

  • School of Air and Missile Defense, Air Force Engineering University, Xi'an 710051, China

  • Received Date: 24 Jun 2013
  • Publish Date: 20 May 2014
    Abstract
  • For the problem of reentry vehicle (RV) tracking, adaptive piecewise constant Jerk model and tracking algorithm were proposed based on kinetics acceleration model and stochastic model approximation. Recursive model of target acceleration was induced by introducing kinetics Jerk model and assumption of piecewise constant Jerk. A new definition and adaption method of process noise was proposed according to the idea of stochastic model approximation. The real-time RV tracking was achieved by divided difference filter based on the augmented state model. Simulation results show that the proposed algorithm has the similar tracking accuracy on stable state as the tracking algorithm based on the piecewise constant acceleration model, but it has better performance on tracking state mutation than the latter.

     

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