针对空间目标检测跟踪中可能存在大量伴飞干扰的问题，提出了一种基于密集多目标运动分组的空间目标快速检测跟踪方法。首先，在传感器分辨率允许的范围内，通过稀疏光流提取目标群体内个体的运动信息，然后利用母函数正则化来整合运动路径之间的相似性，以“集体合并”的思路，从密集随机运动中检测有序群集运动，在空间上将群目标划分为若干个具有相似运动模式的稀疏群组，并以稀疏群组间的拓扑关系构建图模型，筛选出目标群中的疑似目标，最后利用帧间相关性抑制虚警。仿真实验结果表明：对于空间中不同群目标分布场景，该方法具有良好的鲁棒性和实时性。

To cope with the problem of numerous accompanied interference in the field of target detection and tracking in space, a fast detection and tracking method for targets in space based on dense multi-target motion grouping was proposed. Firstly, within the range allowed by the sensor resolution, the sparse optical flow was adopted to extract the motion information of the individual in the group, and then the generating function regularization was used to integrate the similarity between the motion paths. With the idea of “collective merging”, collective motions were detected from dense random motion, so that the group targets can be divided into several sparse groups with similar motion patterns in space. Finally, a graph model based on the topological relationship among sparse groups was constructed to filter out potential targets for which the false alarm was suppressed by inter-frame correlation. Simulation and experiment results show that the proposed method has good robustness and real-time performance for different group targets distribution in space.