Objectives:　Considering　the　inaccurate　separation　of　signal　and　noise　of　empirical　mode　decomposition　(EMD)　method　and　the　uncertainty　of　independent　component　analysis　(ICA),　a　new　method　for　denoising　deformation　data　with　improved　complete　ensemble　empirical　mode　decomposition　(ICEEMD),　independent　component　analysis　(ICA)　and　minimal　distortion　principle　(MDP)　is　proposed.　Methods:　Firstly,　ICEEMD　method　is　used　to　decompose　the　deformation　monitoring　data　effectively,　and　the　virtual　noise　signal　is　constructed.　Secondly,　ICEEMD　decomposition　of　virtual　noise　is　carried　out　to　extract　twice　virtual　noise　signal　which　is　closer　to　real　noise.　The　input　observation　channel　is　composed　of　twice　virtual　noise　and　original　deformation　data　and　processed　by　ICA.　Then,　by　calculating　the　correlation　coefficient　between　the　independent　components　and　the　input　signal　after　ICA　processing,　the　sorting　uncertainty　and　phase　uncertainty　of　independent　components　can　be　solved.　Finally,　the　MDP　criterion　is　used　to　effectively　solve　the　amplitude　uncertainty　of　independent　components.　Results:　Through　the　detailed　analysis　of　noisy　simulation　data　and　actual　bridge　GNSS　deformation　monitoring　data,　the　results　show　that　the　proposed　method　has　achieved　good　denoising　effect　and　can　effectively　improve　the　performance　of　denoising.　Conclusions:　It　also　fully　verified　the　feasibility　and　effectiveness　of　the　proposed　method　indenoising　of　deformation　monitoring　data.　©　2021,　Editorial　Board　of　Geomatics　and　Information　Science　of　Wuhan　University.　All　right　reserved.