Title :
Improved residual resampling algorithm and hardware implementation for particle filters
Author :
Shaohua Hong ; Jianxing Jiang ; Lin Wang
Author_Institution :
Dept. of Commun. Eng., Xiamen Univ., Xiamen, China
Abstract :
In this paper, an improved residual resampling (RR) algorithm and hardware architecture for efficient hardware implementation of particle filters (PFs) is proposed. By rounding the accumulated product of the particle non-normalized weight and the number of particles, the proposed improved RR algorithm avoids the resampling of the residuals and thus has only one loop. Mathematical analysis and simulation results confirm that the proposed algorithm can guarantee the number of resampled particles correct and show approximately equal performance with the traditional systematic resampling (SR) and residual systematic resampling (RSR) algorithms. Compact hardware architecture for the proposed resampling is presented and the bearings-only tracking (BOT) problem is used for illustration and evaluation. Experimental results indicate that this hardware architecture is efficient in terms of low resource usage and low latency.
Keywords :
Monte Carlo methods; particle filtering (numerical methods); signal sampling; BOT problem; bearings-only tracking problem; hardware architecture; hardware implementation; mathematical analysis; number-of-particles; particle filters; particle nonnormalized weight; residual resampling algorithm; sequential Monte Carlo filters; algorithm; hardware architecture; improved residual resampling; particle filters;
Conference_Titel :
Wireless Communications & Signal Processing (WCSP), 2012 International Conference on
Conference_Location :
Huangshan
Print_ISBN :
978-1-4673-5830-9
Electronic_ISBN :
978-1-4673-5829-3
DOI :
10.1109/WCSP.2012.6542909