In human visual system (HVS), is the contrast value occupies the most important part rather than the brightness. The existing infrared small target detection algorithm based on HVS can get a higher signal to noise ratio and detection rate, but it also has shortcomings of higher false alarm rate and easily effected by noise. Considering those shortcomings, An infrared small target detection algorithm based on visual saliency improved by spatial distance is proposed. The gray value of target is weighted by the ratio of the target pixel block and its surrounding blocks, and a saliency map is got. Spatial distance is one of the most important factors in visual attention mechanism and is used in the calculation of the weighted sum of the surrounding blocks. Smaller weight value is distributed to fruther distance according to the weighted space distance. Experimental results show that the proposed algorithm can not only get a lower false alarm rate, but also has robustness for noise.