Segmentalized FCM-based Tracking Algorithm for Zigzag Maneuvering Target

This paper presents a new method for tracking a zigzag maneuvering target by compensating for the positional error of the target. The positional difference between the measured and predicted points is separated into acceleration and noise. Fuzzy c-means (FCM) clustering is utilized as an adaptive method for noise separation. Approximating acceleration is determined by the membership function of the FCM. The approximated acceleration is used to compensate for the tracking error. The procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.