吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (5): 1696-1701.doi: 10.13229/j.cnki.jdxbgxb201505045

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Novel particle filter algorithm based on second-prediction

WU Yong, WANG Jun, CAO Yun-he, ZHANG Pei-chuan   

  1. National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China
  • Received:2014-02-20 Online:2015-09-01 Published:2015-09-01

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Abstract: In order to handle the problem that current observation information is not used in the particle sampling stage of the Particle Filter (PF), a novel particle filter algorithm based on Second-Prediction (SP-PF) is proposed and implemented on the Graphics Processing Unit (GPU). First, sampling from the state transition function is performed to obtain the predicted particles, and by least square estimation, a new generator of sampling particles is constructed. Then, on the basis of the predicted particles, the current observation information is introduced into the secondary particle prediction. After double predictions, each new particle is an unbiased estimate of the current state. Finally, the current state is estimated by means of weighting these particles, and after the completion of state estimation, resampling is conducted. Experimental results demonstrate that the proposed algorithm improves the precision of estimation compared with Standard Particle Filter (SPF), Auxiliary Particle Filter (APF) and Unscented Particle Filter (UPF). Furthermore, the processing efficiency of SP-PF is greatly raised by using GPU.

Key words: information processing technology, particle filter, graphics processing unit, least square estimation

CLC Number: 

  • TN911
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