Classic　postprocessing　time-frequency　analysis　(TFA)　methods　calculated　by　the　short-time　Fourier　transform　(STFT)　suffer　from　the　problems　of　blurry　cross　points　and　unsatisfied　time-frequency　concentration　under　noise　interference.　For　solving　the　problems,　a　novel　TFA　technique,　termed　adaptive　scaling　demodulation　transform　(ASDT),　is　developed　in　this　article.　The　ASDT　aims　to　calculate　ideal　time-frequency　representation　(TFR)　by　adaptively　estimating　the　instantaneous　frequency　(IF)　curves,　extracting　the　time-frequency　amplitudes　at　the　estimated　IF　curves,　and　reassigning　these　time-frequency　amplitudes　into　a　new　TFR.　The　IF　curves　are　adaptively　estimated　by　constructing　the　scaling　demodulation　operator　and　maximum　criterion　of　local　spectrum　amplitude.　The　time-frequency　amplitudes　at　the　calculated　IF　curves　are　selected　from　the　STFT　result.　In　this　way,　the　ASDT　can　eliminate　smeared　time-frequency　amplitudes　and　background　noise　and　accurately　characterize　intersecting　frequency　ridges　with　high　energy　concentration.　The　effectiveness　of　the　developed　technique　is　verified　through　simulated　signal　and　two　different　mechanical　vibration　signals.　Comparison　analysis　with　classic　TFA　techniques　shows　that　the　ASDT　has　much　better　ability　for　processing　signal　with　intersecting　frequency　curves　under　noise　interference.