To solve the infrared target real-time detection problems caused by low signal to noise ratio with complex background, an infrared small target detection method based on correlation filter is proposed. The small target detection problem is transformed into pattern classification task, which consists of two stages: off-line training and on-line detection. In training stage, a correlation filter is obtained using the training dataset produced by two-dimensional Gaussian model. It has ability to distinguish target and background. In detection stage, the sub-image blocks of the infrared image are extracted successively and the filtering response confidence map which indicates the target location is computed. The experiments under two conditions demonstrate that the proposed method not only has better detection performance with effective reduction of the false alarm rate, but also has better real-time performance.