A Novel Method for Tracking and Recognizing Infrared Dim and Small Moving Target Based on Modified Probabilistic Data Associating Filter
基于改进概率数据关联滤波的红外小运动目标跟踪

During tracking dim and small moving targets in the electrooptical detecting system, many false alarms extracted in the tracking window for low signal-to-noise ratio and high false alarm ratio debase seriously the performance of target recognition and tracking. To solve this problem, the target characters of the infrared imaging tracking system are analyzed, and based on the idea of the probabilistic data association filter, a modified method, which integrates the continuity and consistency of target’s amplitude and motion, is proposed. The emphases are laid on the comparison of the target recognition and tracking performances between the original maximum likehood-probabilistic data associated filter and the proposed method. Some experimental results are included and the performance of target recognition and tracking target is improved greatly.