This　article　proposed　a　simple　and　effective　methodology　for　improving　diversity　of　samples　in　Particle　Filter　(PF).　The　motivation　lies　in　the　situation　that　resampling　procedure　which　aims　for　amending　particle　degeneracy　always　leads　to　particle　depletion　and　less　diversity　of　particles　has　severe　consequence　on　the　filter　estimation　accuracy.　Various　resample　approaches　have　been　developed　in　recent　years,　including　multi-nominal　resample,　residual　resample,　stratified　resample　and　systematic　resample.　All　of　them,　however,　will　inevitably　lead　to　lose　of　diversity　in　scatter　of　particles　because　they　simply　replace　lower　weighed　particles　with　higher　weighed　particles.　In　this　paper,　we　developed　practical　MCMC　solutions　for　drawing　particles　for　PF.　The　selections　of　proposal　distribution　and　convergent　chain　node　are　taken　into　careful　considerations.　It　is　revealed　from　the　simulations　and　real　experiment　that　the　proposed　resampling　method　is　capable　of　improving　the　performance　of　Particle　Filter.　©　2011　IEEE.