基于代数图论的修正贝叶斯群目标航迹起始算法

群目标跟踪技术是测量空中集群生物目标飞行状态的有效手段，而航迹起始是群目标跟踪的第1步，包括分群检测与航迹确认。针对现有算法在分群检测时限制群内目标必须两两相似，在航迹确认时因等效量测残差过大导致航迹误丢弃的问题，该文提出一种基于代数图论的修正贝叶斯群目标航迹起始算法，通过引入代数图论实现监测空间内量测集合的划分，通过修正经典贝叶斯算法的似然比定义避免航迹的误丢弃。实测数据处理结果证明该算法具备准确划分各个子群并快速起始各子群航迹的能力。

Modified Bayesian Group Target Track Initiation Algorithm Based on Algebraic Graph Theory

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.