Real-Time tracking low-contrast target in the complex environment is a key problem in the visual area. The algorithm needs to not only copy with the high similar between target and background, revolution, scale variations and target occlusions but also satisfy the real-time tracking. This paper provides a method based on the likelihood similarity function to resolve the low-contrast tracking. In the model construction phase, the new method uses the single peak of the pyramid surface equation to enhance the target information. In the model matching phase, it innovates a new likelihood similarity function which provides more distinguishable measurements than the traditional one. Finally, the tracking process transforms to the maximum likelihood estimate. The algorithm is applied in the TMS320C6416 hardware system and successfully copes with the low contrast (LSCR=4.9) airplane in the cluster background. A series of experiments results show that the lowest limitation of tracking the target by the proposed method is about 3 (LSCR value).