Paper Title:
A Novel Modified Particle Filter Algorithm
  Abstract

The particle filter (PF) algorithm provides an effective solution to the non-linear and non-Gaussian filtering problem. However, when the motion noises or observation noises are strong, the degenerate phenomena will occur, which leads to poor estimation. In this paper, we propose a modified particle filter (MPF) algorithm for improving the estimated precision through a particle optimization method. After calculating the coarse estimation with the traditional PF, we optimize the particles according to their weights and relative positions, then, move the particles toward the optimal probability distribution. The state estimation and target tracking experiments demonstrate the outstanding performance of the proposed algorithm.

  Info
Periodical
Advanced Materials Research (Volumes 204-210)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
1895-1899
DOI
10.4028/www.scientific.net/AMR.204-210.1895
Citation
Q. H. Gao, J. Wang, M. L. Jin, "A Novel Modified Particle Filter Algorithm", Advanced Materials Research, Vols. 204-210, pp. 1895-1899, 2011
Online since
February 2011
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Price
$32.00
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