With the development of infrared imaging guided systems, higher requirements are put forward to the precision and real-time performance of guided tracking algorithms. Currently, guided systems have been required to output tracking results within 20 ms. Although some tracking algorithms have good tracking effectiveness, they can not output their tracking results in real time. Since the classical correlating tracking algorithm is mainly based on pixel gray-level features, the tracking point drift problem caused by the rotation, expansion and translation of the target in the process of tracking can not be solved. To solve the problem that the classical correlation tracking algorithm can not operate stably when the image is rotating and the tracking point drift problem present when the target image is expanding quickly, the invariable moment features of images are studied. The features of rotation-scale-translation invariance of images are used to choose the suitable invariant moment features for tracking. The tracking algorithm is designed by using the multiplication correlating function and the template update function based on correlation coefficient. The problem that the infrared target of which the size and shape are changed in complex and yawp environment can not be tracked stably is solved.