A kind of adaptive optimization algorithm for particle filter
Abstract：By analyzing two techniques, namely, proposal distribution and resampling, an adaptive optimiza- tion algorithm for particle filter is presented. Firstly, hybrid proposal distribution is adaptively optimized based on anneal parameter in order to improve the sampling range of proposal distribution, se＇condly, based on the a- daptive resampling techniques on effective sample size, auother diversity measure, namely population factor, is used to adaptively adjust the resampling threshold. Moreover, the particle mutation operation is integrated into PF after resampling so as to ensure the diversity of particle sets. finally, an improved partial stratified re- sampling （PSR） algorithm in PF is studied, which keeps the advantage of PSR in implementation speed and time and improves the pefrmance of PF with weight optimization. Throngh simulation experiments, validity of the proposed method is verified.
Keywords：particle filteradaptive optimizationanneal parameterhybrid proposal distributiondiversity meas-ureresampling threshold
Publication Date：2012-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 201-206 )