Moving　object　detection　is　a　key　point　in　dynamic　environment　perception.　Occupancy　grid　mapping　is　a　practical　approach　for　the　dynamic　environment　perception.　Different　moving　object　detection　methods　in　the　occupancy　grid　map　are　proposed　aiming　at　four　uncertain　reasoning　algorithms　in　the　Bayesian　framework　and　the　evidential　framework.　The　moving　object　detection　methods　are　comparably　analyzed　by　simulation,　and　they　are　also　tested　on　real　range　data　of　the　outdoor　dynamic　environment　acquired　by　a　multi-layer　laser　scanner.　Experiment　results　show　that,　by　comparing　with　the　local　map　at　the　current　moment　and　the　global　map　at　the　former　moment,　the　original　Bayesian　inference　and　the　classical　Dempster＇s　rule　of　combination　are　able　to　clearly　and　wholly　detect　the　moving　objects,　and　filter　out　the　measurement　noise　in　static　objects　and　free　space.　©,　2014,　Xi　Tong　Gong　Cheng　Yu　Dian　Zi　Ji　Shu/Systems　Engineering　and　Electronics.　All　right　reserved.