The　existing　speech　enhancement　algorithm　has　shown　poor　performance　under　low　Signal　Noise　Ratios　(SNRs).　To　resolve　this　problem,　a　speech　enhancement　algorithm　based　on　binaural　sound　source　localization　and　cosh　measure　filtering　is　proposed.　Firstly,　the　algorithm　uses　a　sound　source　localization　algorithm　based　on　head　correlation　functions　and　two-level　deep　learning　to　extract　the　spatial　information　of　the　binaural　sound　source　and　determine　the　spatial　position　of　the　sound　source.　The　beamforming　method　is　then　used　to　remove　the　noises　in　different　directions　from　the　speech.　Finally,　the　Wiener　filtering　of　cosh　measure　based　on　logarithmic　relation　is　used　to　remove　the　noise　in　the　same　direction　as　the　speech　to　achieve　speech　enhancement.　Experiments　show　that　the　proposed　algorithm　has　better　robustness　and　denoising　ability　than　the　contrast　algorithms.