One　of　the　main　reasons　that　affecting　the　stability　of　power　systems　is　low　frequency　oscillation　(LFO).　The　existence　of　noise　influences　the　accuracy　of　LFO　mode　identification　extracted　from　wide-area　measurement　system　(WAMS).　The　wavelet　threshold　de-noising　is　widely　used　in　signal　processing.　In　this　paper,　wavelet　soft　threshold　is　illustrated　to　attenuate　the　noise　of　LFO　signal,　the　optimal　wavelet　basis　and　decomposition　level　for　de-noising　LFO　signal　with　noise　are　obtained　and　verified　by　experiments.　Following　the　signal　de-noising,　an　improved　Matrix　Pencil　(MP)　algorithm　is　used　for　mode　identification　of　LFO.　This　improvement　particularly　lies　in　the　ratio　of　adjacent　singular　entropy　increment　difference　(RASEID)　designed　as　an　adaptive　order　determination　method　in　the　MP　algorithm　proposed　in　the　paper.　RASEID　not　only　makes　the　MP　algorithm　adaptive,　but　also　enhances　the　stability　of　the　order　determination　in　the　mode　identification　process.　The　proposed　method　ensures　the　accuracy　of　mode　identification　with　lower　sensitivity　to　noise　interference.　Finally,　the　validity　of　the　proposed　method　is　verified　by　three　cases　studies.　The　first　study　is　on　the　analysis　of　synthetic　signal　typically　performed　in　many　literatures.　The　second　study　is　to　identify　the　mode　of　active　power　LFO　signal　which　is　generated　by　IEEE　four-generator　and　two-area　system　given　with　disturbance　on　RT-LAB　experimental　platform.　The　third　study　is　the　oscillation　analysis　of　the　actual　LFO　data　in　the　North　American　power　grid.　The　results　validate　the　feasibility　of　the　proposed　method　for　mode　identification　of　noisy　LFO.