A　method　of　vehicle　identification　and　tracking　based　on　radar　ranging　is　proposed　in　this　paper　to　accurately　identify　vehicle　objects　on　road.　Firstly　a　clustering　analysis　is　conducted　on　data　collected　with　an　adaptive　distance　threshold,　and　iterative　end　point　fitting　(IEPF)　algorithm　is　adopted　to　extract　line　segments　within　a　cluster.　On　this　basis　the　feature　vector　of　object　is　obtained,　with　which　vehicle　object　is　identified.　Then　by　calculating　the　cost　function　of　feature　vector,　multi-object　association　is　performed,　and　based　on　the　results　of　association　the　state　of　object　is　updated　with　Kalman　filter.　Finally　a　verification　test　of　the　method　is　performed　on　the　road　in　campus　by　an　intelligent　vehicle　BJUT-IV　with　laser　radar　LMS291.　The　results　show　that　the　method　proposed　can　accurately　track　multiple　moving　vehicles.　©,　2014,　Qiche　Gongcheng/Automotive　Engineering.　All　right　reserved.