This　paper　motivates　to　solve　the　multiple　mapping　of　Received　Signal　Strength　Indications　(RSSIs)　and　location　estimating　problem　in　mobile　positioning.　A　mobile　positioning　method　based　on　Time-distributed　Auto　Encoder　and　Gated　Recurrent　Unit　(TAE-GRU)　is　proposed　to　realize　the　mobile　positioning.　To　distinguish　the　identical　RSSI　of　different　temporal　steps,　this　paper　develops　a　reconstructed　model　based　on　Time-distributed　Auto　Encoder　(TAE),　which　is　conducive　for　further　learning　of　the　estimated　model.　Among　them,　time-distributed　technology　is　utilized　to　translate　the　data　of　each　temporal　step　separately　accommodating　the　temporal　characteristics　of　RSSI　data.　Besides,　an　estimated　model　based　on　Gated　Recurrent　Unit　(GRU)　is　developed　to　learn　the　temporal　relationship　of　RSSI　data　to　estimate　the　locations　of　mobile　devices.　Combining　the　TAE　model　and　GRU　model,　the　proposed　model　is　provided　with　the　capability　of　solving　multiple　mapping　and　mobile　positioning　dilemma.　Massive　experimental　results　demonstrated　that　the　proposed　method　provides　superior　performance　than　comparative　methods　when　solving　multiple　mapping　and　positioning　problems.　©　2021　ACM.