基于代数图论的修正贝叶斯群目标航迹起始算法

Group target tracking is an efficient method to measure the states of airborne flocks. The first step of group target tracking is track initiation, including target clustering and track promotion. The state-of-the-art algorithms require mutual similarity between targets for clustering procedure, and track may be wrongly rejected due to the large residual of equivalent measurement. A modified Bayesian group track initiation algorithm based on algebraic graph theory is proposed. The clustering of measurement sets in surveillance volume is achieved by introducing the algebraic graph theory. The rejection of true track is avoided by modify the definition of classical Bayesian likelihood ratio. Results from actual field tests demonstrate the capability of clustering group targets precisely and promoting group tracks effectively.