Aiming at shortcomings of more iterative times

sample size tends to decay and diversity of observed values is poor of traditional Monte Carlo（ MC） mobile localization

an improved localization method for mobile wireless sensor networks（ WSNs） based on population MC localization（ PMCL） method is proposed. Two-constrains are proposed to decrease iterative times and PMC is introduced to match resampling precisely. Based on node density

anchor node distribution proportion and sample number and other parameters

theoretical analysis and experimental simulation on PMCL scheme are carried out. Performance comparisons of PMCL with other sequential Monte Carlo（ SMC）-based schemes are carried out. Simulation results show that delay of PMCL scheme has some superiority to those of other schemes

and accuracy is improved in some cases of lower node moving velocity and larger node density.