With　the　technical　advances　of　wireless　sensor　networking　and　smart　mobile　device,　the　demand　for　position　information　of　pedestrians　(especially　in　the　indoor　environment)　has　increased　remarkably.　In　this　paper,　we　proposed　an　indoor　localization　approach　based　on　received　signal　strength　(RSS)　and　Bayesian　filter.　In　the　following　sections,　we　describe　our　virtual　modeling　method　of　environment　and　the　way　we　take　object＇s　movement　sequences　as　history　conditions　in　Bayesian　filter.　The　experiment　results　show　that　our　solution　provides　accurate　tracking　results　(within　80　centimeters　for　moving　object).　The　contribution　of　this　research　is　that　it　provides　a　general　implementation　utilizing　Bayesian　filter　which　is　able　to　estimate　location　precisely　with　off-the-shelf　hardware.　And　Bluetooth　Low　Energy　(BLE)　is　employed　which　reduces　power　consumption　considerably.　Meanwhile　the　accuracy　is　sufficient　for　pedestrian　tracking　in　real　application　scenarios　where　BLE　devices　can　be　easily　deployed.