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《Journal of Xi'an Jiaotong University》 2010-06
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Gaussian Diffracted Particle Filter

NING Xiaolei1,WANG Hongli1,NING Yuqi2,ZHANG Qi1(1.Controlling and Testing Department,The Second Artillery Engineering College,Xi′an 710025,China;2.School of Economics and Finance,Xi′an Jiaotong University,Xi′an 710061,China)  
The particle filter combined with Gaussian filter can restrict particle degeneracy with a secondary result that the new particle filter has a high calculation cost.In order to reduce the expensive calculation cost in the Gaussian aided particle filter(GAPF),a Gaussian diffracted particle filter(GDPF) is proposed by introducing a light-diffracting-like particle diffracting sampling method into the current GAPF.The proposed method predicts fewer particles,and keeps more particles to be re-sampled from each Gaussian importance density function,so that the overall particles in the estimation of the system state are maintained the same by extending and contracting of particles.The number of particles is also adjusted according to particle weights.Therefore the calculation cost in GDPF is significantly reduced when the accuracy is required the same as the GAPF method,and the sample degeneracy problem is successfully improved.Theoretical analysis indicates that the efficiencies of both GDPF and GAPF are the same.The results of Monte Carlo simulations with the same number of particles in state estimation show that the improved particle filter can preserve the same accuracy of estimation while computation burden is greatly reduced.
【Fund】: 国防预研项目(51309060302)
【CateGory Index】: TN713
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