Of　the　existing　sound　source　localization　algorithms　for　digital　hearing　aids,　the　accuracy　is　low　while　the　computational　complexity　is　high.　To　solve　these　problems,　a　new　binaural　sound　source　localization　algorithm　was　proposed.　First,　the　collected　binaural　sound　signals　were　decomposed　into　several　subband　signals　by　the　Gammatone　filter,　and　the　data　was　compressed　according　to　the　energy.　Then,　the　binaural　cues　contained　in　the　head-related　transfer　function　(HRTF),　namely　interaural　time　difference,　interaural　level　difference,　and　interaural　coherence,　were　extracted　to　characterize　the　position　of　the　sound　source.　Finally,　the　source　location　was　estimated　by　the　Gaussian　mixture　model　(GMM)　classifier.　Experiment　results　show　that　the　proposed　algorithm　has　high　accuracy,　strong　robustness,　and　low　complexity.　©　2018,　Editorial　Department　of　Journal　of　Beijing　University　of　Technology.　All　right　reserved.