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Volume 40 Issue 8
Aug.  2014
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Journal of Beijing University of Aeronautics and Astronautics  > 2014  >  40(8): 1102-1108.
Li Zhenxing, Liu Jinmang, Bai Dongying, et al. Group targets tracking algorithm based on strong tracking filter and improved weighted method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(8): 1102-1108. doi: 10.13700/j.bh.1001-5965.2013.0650(in Chinese)
Citation: Li Zhenxing, Liu Jinmang, Bai Dongying, et al. Group targets tracking algorithm based on strong tracking filter and improved weighted method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(8): 1102-1108. doi: 10.13700/j.bh.1001-5965.2013.0650(in Chinese)
shu

Group targets tracking algorithm based on strong tracking filter and improved weighted method

doi: 10.13700/j.bh.1001-5965.2013.0650

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

  • Received Date: 14 Nov 2013
  • Publish Date: 20 Aug 2014
    Abstract
  • To improve the estimation performance of the existing interactive multiple models tracking algorithm for group targets, an improved group tracking algorithm was proposed. Firstly, by using the adaptive algorithm of model transition probability, the optimization of real-time matching for tracking models with the actual motion pattern was performed. And a fading factor of strong tracking filter was used to improve the estimation accuracy of the centroid state in the maneuvering stage. Then the fusion estimation of centroid state and extension state were implemented by using the probability weighted method and the scalar coefficients weighted method, respectively. Lastly, the implementation steps of the new tracking algorithm were presented in detail, which were based on variational Bayesian filtering algorithm. The computer simulations show that the estimation accuracy of the centroid state and extension state is improved in the new algorithm, and this algorithm can reduce a great deal of peak error in the maneuvering stage.

     

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