主被动传感器实时信息融合的STMHM算法

 主、被动传感器实时信息融合是同时实现目标跟踪和目标识别的重要途径,构建STMHM(空时二维多假设模型)算法来解决该问题.首先,设计主、被动传感器的融合数据模型,并分别构建两类传感器的目标量测空间,设计STMHM的融合空间;其次,提出主、被动传感器量测空间时间初始化方法,并设计模型的滤波算法,给出适应于该算法的信息融合评判规则;最后,设计空中态势,运用该算法对数据进行融合,验证算法的有效性.

STMHM Algorithm of Active and Passive Sensors Real-Time Data Fusion

Real time data fusion of airborne active and passive sensors was an important technique achieving targets track and recognition.The spatial time multiple hypothesis model (STMHM) algorithm was brought forward to solve the problem.The data-model was respectively constructed for active and passive sensors according to observed data.Fusion-space of STMHM was built upon the active and passive sensors targets-observed-spaces designed from the data-models.Time initialization method was put forth.Filtering algorithm and judgment rules were discussed.We design an aerial situation data,and then use the algorithm to fuse these data and analyze the validity of the algorithm.