The invention discloses a binaural sound source localization method based on deep learning in a digital hearing aid. First, binaural sound source signals are decomposed into several channels through a gammatone filter, and high-energy channels are extracted through weighting coefficients, and then the head correlation function ( head‑related‑transform function, HRTF) extracts the first type of features, that is, Interaural Time Difference (Interaural Time Difference, ITD) and Interaural Intensity Difference (Interaural Intensity Difference, IID) as the input of deep learning, and divides the horizontal plane into four Quadrant to narrow down the targeting. Then extract the second type of features of head-related transmission, namely, the interaural level difference (Interaural Level Difference, ILD) and the interaural phase difference (Interaural Phase Difference, IPD). Finally, in order to obtain more accurate positioning, the first type and The four features of the second category are used as the input of the next deep learning, so as to obtain the azimuth angle of the sound source localization. Realize the precise positioning of 72 azimuth angles from 0° to 360° on the horizontal plane with a step size of 5°.