RSSI　wireless　signal　is　a　reference　information　that　is　widely　used　in　indoor　positioning.　However,　due　to　the　wireless　multipath　influence,　the　value　of　the　received　RSSI　will　have　large　fluctuations　and　cause　large　distance　error　when　RSSI　is　fitted　to　distance.　But　experimental　data　showed　that,　being　affected　by　the　combined　factors　of　the　environment,　the　received　RSSI　feature　vector　which　is　formed　by　lots　of　RSSI　values　from　different　APs　is　a　certain　stability.　Therefore,　the　paper　proposed　RSSI-based　fingerprint　feature　vector　algorithm　which　divides　location　area　into　grids,　and　mobile　devices　are　localized　through　the　similarity　matching　between　the　real-time　RSSI　feature　vector　and　RSSI　fingerprint　database　feature　vectors.　Test　shows　that　the　algorithm　can　achieve　positioning　accuracy　up　to　2-4　meters　in　a　typical　indoor　environment.　©　2015　Aiguo　Zhang　et　al.