Indoor　localization　and　tracking　have　attracted　growing　attention　because　of　its　widely　application　for　indoor　location-based　services　(LBSs).　However,　for　indoor　localization,　only　with　single　positioning　technology,　the　positioning　accuracy,　and　localizability　are　difficult　to　satisfy　the　requirement　due　to　the　complex　and　crowed　indoor　environment.　An　indoor　cooperative　localization　and　tracking　algorithm　(CLTA)　based　on　grid　is　developed　to　solve　above　problems.　The　CLTA　is　divided　into　offline　phase　and　online　phase.　In　the　offline　phase,　a　cooperative　localization　fingerprint　database　is　established　based　on　reliable　nodes.　In　the　online　phase,　a　region　overlapping　mechanism　is　used　to　narrow　location　area　in　multi-network　surroundings　at　first.　Then,　we　use　a　prediction　mechanism　to　predict　the　mobile　target　position　in　order　to　further　narrow　the　location　area.　At　last,　a　cross　grid　strategy　is　used　to　update　the　data　in　fingerprint　database　if　possible,　aiming　at　improving　the　accuracy　of　localization.　Simulation　and　experiment　results　show　that　the　proposed　algorithm　is　better　than　single　network　localization　algorithm　on　localization　and　tracking　performance.　©　2013　IEEE.