多雷达多目标航迹关联算法大多量测数据中因信息贫瘠的原因导致雷达目标航迹关联精确度较差、性能较低等一系列问题。基于灰色关联分析理论的航迹关联算法，分析研究了综合性线段Hausdorff距离(LHD)灰色关联方面的理论，并将其用在雷达航迹关联领域。通过仿真证明，该算法能够综合考虑航迹之间的距离远近度和2条航迹曲线的拟合度。特征辅助信息不仅可以用于数据关联，也可以用在航迹关联方面。提出基于目标特征辅助信息的序贯灰色关联算法，仿真证明该算法与传统灰色关联算法相比精确度较高，能够在工程实践中提高关联概率。

For multiple radar target track correlation algorithm, the barren information in most measurement data leads to many problems including poor accuracy of radar target correlation and the low performance. According to the track correlation algorithm based on the theory of grey correlation analysis，the comprehensive Line segment Hausdorff Distance(LHD) grey correlation theory is analyzed and applied in the field of radar correlation. The simulation proves that the algorithm can comprehensively consider the distances among different tracks and the curve fitting for two tracks. Feature auxiliary information can not only be used for data association, but also for track association. In this paper, sequential grey association algorithm based on target feature auxiliary information is proposed. Simulation indicates that this algorithm has higher accuracy compared with traditional grey association algorithm and can improve the correlation probability in engineering practice.