Title :
A Novel Particle Filter Based on Propagation and Prediction
Author :
Xiangfeng, Bai ; Aihua, Li ; Jialei, Li ; Taiyang, Liu
Author_Institution :
502 Fac., Xi´´an Inst. of High Technol., Xi´´an, China
Abstract :
The problems existing in standard particle filter include large computation and particle degeneration, and a novel particle filter based on propagation and prediction is proposed to solve the problems. In this method, particles after state transition are propagated according to the distribution of state noise, and then the generated filial particles are used to predict corresponding mother particles referring to measurement, then the latest measurement information is fused into estimation. Therefore, the predicted particles are closer to the true state, and the accuracy of particle filter is improved. The efficiency of the algorithm has been proved by experimental results, and the algorithm occupies great predominance with fewer particles.
Keywords :
electromagnetic wave propagation; particle filtering (numerical methods); prediction theory; state estimation; particle degeneration; propagation-prediction particle filter; state noise distribution; Accuracy; Estimation; Filtering algorithms; Noise; Particle filters; Prediction algorithms; importance probability density function; particle degeneration; particle filter; state estimation;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on
Conference_Location :
Shangshai
Print_ISBN :
978-1-4244-9010-3
DOI :
10.1109/ICMTMA.2011.56
