MHT(多假设跟踪)是一种基于多个扫描周期量测, 进行数据互联的技术, 理论上是解决数

据关联的最优方法。文中重点阐述多假设跟踪算法中数据聚簇、假设生成及假设概率计算、假设约简与

剪枝等环节。从工程角度出发, 采用K􀀁 best最优假设和N􀀁 scan 回溯剪枝以提高算法效率和实用-MHT (multiple hypothesis tracking) is a kind of multiple scan cycle measurement based, data interconnection technology, theory is to solve the number

According to the optimal method of association. This paper focuses on multiple hypothesis tracking algorithm in data clustering, hypothesis generation and hypothesis probability calculation, assuming that reduction and

The pruning process. From the engineering point of view, using K 􀀁　best optimal hypothesis and N 􀀁　scan backtracking pruning algorithm to improve the efficiency