基于统计双门限的中断航迹配对关联算法

摘要

针对现有经典的中断航迹关联算法在目标密集、航迹交叉或分岔环境下关联正确率低和实用性差的问题，该文提出了基于统计双门限的中断航迹配对关联算法。该算法引入统计双门限原理，增加了χ2分布门限检测的关联样本数，对复杂环境具有更强的适应能力。仿真验证表明，在空中飞行目标航迹交叉环境和弹道目标环境下，该文算法的全局正确关联率和平均正确关联率均比经典算法有显著提高，验证了该算法性能的优越性。%The classical Track Segment Association (TSA) algorithm suffers from low accuracy and is impractical to use in concentrated targets, branching, and cross-tracking environment. Thus, a new statistical binary track segment association algorithm is proposed. The new algorithm is more appropriate as it increases the sample size for the2χdistribution threshold detection. Simulation results show that in air cross tracking and for ballistic targets, the global correct association rate and the average correct association rate of the proposed algorithm are remarkably improved, which proves the good performance of the proposed algorithm.