The rosette-scanning infrared seeker (RSIS) is a tracker that a single infrared detector scans the total field of view (TFOV) in a rosette pattern, and then produces 2D image about a target. Since the detected image has various shapes in accordance with the target position in the TFOV, it is difficult to determine a precise target position from the obtained image. In order to track this type of target, therefore, we propose an efficient tracking method using the K-means algorithm (KMA). The KMA, which classifies image clusters and calculates their centers, is used to cope with an countermeasure (CM) such as an IR flare. To evaluate the performance of the RSIS using the KMA dynamically, we simulate the RSIS in the various conditions, and discuss the tracking results.