On-Line State Estimation of Maneuvering Objects by Sequential Monte Carlo Algorithm

  • Authors:

  • Donka S. Angelova;E. Semerdjiev;Tzvetan Semerdjiev;Pavlina D. Konstantinova

  • Affiliations:

  • -;-;-;-

  • Venue:
  • LSSC '01 Proceedings of the Third International Conference on Large-Scale Scientific Computing-Revised Papers
  • Year:
  • 2001

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Abstract

A stochastic sampling algorithm for recursive state estimation of nonlinear dynamic systems is designed and realized in this study. It is applied to the problem of tracking two maneuvering air targets in the presence of false alarms. The performance of the proposed algorithm is evaluated via Monte Carlo simulation. The results show that the nonlinear Bayesian filtering can be efficiently accomplished in real time by simple Monte Carlo techniques.