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In noisy and reverberant acoustic environments, the performance of sound source azimuth localization based on binaural time difference is severely degraded. To solve this problem, a binaural sound source localization algorithm based on subband selection and DBSCAN is proposed. Firstly, the binaural sound source signal is decomposed into several subband signals by using Gammatone filter; secondly, the number of subband channels is compressed according to the subband energy; Sub-band interference; then the sub-band signal is divided into frames, and the data points at the peak are obtained according to the cross-correlation algorithm; finally, the DBSCAN algorithm is introduced to eliminate the influence of noise points and obtain the optimal data points, so as to determine the target sound source according to the ITD positioning model. Azimuth. The experimental results show that the algorithm can significantly improve the azimuth angle localization performance of binaural sound sources compared with the traditional cross-correlation algorithm in complex acoustic environments.