In　this　paper,　we　propose　an　improved　subspace　method　for　speech　enhancement　in　the　presence　of　colored　noise,　based　on　a　novel　prewhitening　technique.　The　colored　noise　modeled　as　autoregressive　(AR)　process　is　first　used　for　the　AR　parameter　estimation.　Then　the　speech　model　in　colored　noise　is　changed　into　the　one　in　white　noise,　by　multiplying　the　noisy　speech　by　the　whitening　matrix　constructed　by　the　AR　parameters.　Because　of　the　novel　prewhitening　technique,　the　proposed　subspace　method　for　speech　enhancement　can　efficiently　deal　with　colored　noise.　Compared　with　existing　subspace　method,　the　proposed　subspace　method　overcomes　difficulty　in　estimating　covariance　matrix　of　colored　noise.　Simulation　shows　that　the　proposed　approach　has　better　performance　than　three　conventional　algorithms.　©　2013　IEEE.