To resolve the problem of the high false alarm rate of traditional adaptive target detection methods of infrared night vision, an adaptive small target detection method of infrared night vision based on sliding window is proposed. First of all, the Harris hawk optimization algorithm is enhanced with combination of teaching learning based optimization algorithm, in order to enhance its ability of escaping from local optimal, a mixed multiple population Harris hawk optimization algorithm is designed; Secondly, a fitness function of small target based on sliding window is designed; Finally, the infrared night vision small target is detected adaptively. Experimental results based on public datasets suggest that, compared to the other adaptive infrared small target detection method, the proposed method has lower false alarm rate for small target detection.