Track-before-detect algorithm based on dynamic programming for multi-extended-targets detection

摘要

In recent years, multi-extended-targets detection in sea clutter has gained a special interest. Dynamic programming based track-before-detect (DP-TBD) algorithm is used to detect extended targets in video data of high resolution radars. Two innovations are presented in this work. First one is a novel partition method to cluster targets into well separate groups for the problem of high-dimensional maximisation. Second one is a novel merit function specifically designed for extended targets for the problem of target extended. Both the principle of this novel DP-TBD method specifically for extended targets and its detail implementation are presented. Then, both the real data and simulated data are performed. The comparison of the results shows that compared with particle filter based track before detect algorithm, the proposed method obtains better performance in detection rate, position error and false alarm rate. Meanwhile, far less calculation is spent with the novel partition method. Therefore, it can safely conclude that the proposed method is very practical under various sea conditions in the real world.