In　view　of　the　fact　that　Dempster-Shafer　(D-S)　evidence　theory　is　unable　to　fuse　data　of　multiple　different　kinds　of　sensors,　an　improved　D-S　evidence　theory　method　based　on　the　fusion　of　support　and　confidence　entropy　is　proposed.　Firstly,　the　identification　framework　of　evidence　theory　is　improved;　secondly,　Spearman　correlation　coefficient　is　introduced　to　represent　the　correlation　between　evidences;　thirdly,　a　new　confidence　entropy　is　defined　to　describe　the　inconsistent　uncertainty　and　nonspecific　uncertainty　between　evidences;　then,　the　evidence　set　is　modified　by　the　combination　of　correlation　and　confidence　entropy;　finally,　Dempster　combination　rule　is　used　for　information　fusion.　The　simulation　results　confirm　that　the　improved　method　of　D-S　evidence　theory　is　feasible　and　more　effective　than　the　traditional　algorithm.