In　this　paper,　we　present　an　adaptive　multi-feature　matching　method　for　target　detection　and　target　tracking　based　on　an　occupancy　grid　map　in　dynamic　outdoor　environments　on　a　moving　vehicle　equipped　with　laser　radar.　The　raw　scanning　points　are　divided　into　blocks　and　the　matching　strategy　of　ICP　(Iterated　Closest　Points)　algorithm　is　modified　by　using　the　multi-feature　information　of　objects.　We　introduce　a　method　to　adaptively　correct　the　weighting　coefficients　of　the　multi-feature　in　the　similarity　function.　After　matching　the　objects　in　the　two　adjacent　frames,　the　online　grid　map　is　updated　by　Bayesian　theory　and　the　probability　of　inverse　sensor　model.　The　moving　objects　are　detected　with　grid　map　matching.　Then,　the　moving　targets　are　finally　tracked　by　tracker　management　coupled　with　Kalman　filter.　In　the　experiment,　the　online　grid　map　is　established　and　the　stable　results　for　targets　tracking　are　also　achieved.