一种新的改进粒子滤波算法

doi:10.3969/j.issn.1001-2400.2010.05.015

Abstract

Abstract:

The sample degeneracy is the critical problem existing in the particle filter. In order to solve this problem, a new combined particle filter algorithm, based on the genetic simulated annealing algorithm and unscented Kalman filter algorithm, is presented in this paper. In the proposed algorithm, unscented Kalman filter algorithm is used to generate the importance proposal distribution which can match the true posterior distribution more closely, and the genetic simulated annealing algorithm based upon the survival-of-the-fitness principle is applied to enhance the diversity of samples. Simulation results indicate the effectiveness and feasibility of the proposed algorithm.

Key words: particle filter, unscented Kalman filter, proposal probability density, genetic annealing simulated algorithm

YANG Lu;LI Ming;ZHANG Peng. New improved particle filter algorithm[J].J4, 2010, 37(5): 862-865+883.

References

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New improved particle filter algorithm

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