Radio　tomographic　imaging　(RTI)　system　needs　to　have　enough　observed　samples　to　ensure　the　performance　of　reconstruction.　The　method　based　on　compressed　sensing　(CS)　can　effectively　solve　the　problem　of　insufficient　observed　samples.　However,　this　method　cannot　solve　the　problem　that　wireless　signals　in　RTI　network　are　affected　by　environmental　noise,　which　results　in　the　decrease　of　positioning　accuracy.　To　solve　this　problem,　we　analyzed　the　characteristics　of　the　received　signal　strength　(RSS),　used　the　Gaussian　mixture　model　(GMM)　to　determine　the　acquired　RSS　observation　samples　to　obtain　the　effective　link　in　the　wireless　network,　and　then　reconstructed　it　by　the　alternating　direction　multiplier　method　(ADMM).The　experimental　results　show　that　when　the　voxel　size　is　set　as　δ=　0.11m　,　the　average　positioning　accuracy　is　improved　by　36%　and　9%,　respectively,　compared　with　the　classical　orthogonal　matching　pursuits　(OMP)　algorithm　and　Tikhonov　algorithm.　In　the　case　of　the　same　data,　the　reconstruction　time　based　on　GMM-ADMM　algorithm　is　only　0.06　seconds,　which　is　conducive　to　the　real-time　performance　of　the　system.　©　2021　IEEE.