摘要
为解决有源无源量测数据因不同步、不同维而难以融合的问题,提出基于时空特征关联的有源无源数据融合方法。首先对目标跟踪模型和时间对准模型进行介绍,然后采用单帧模糊聚类的空域关联方法计算关联置信度,采用多帧D-S证据理论的时域关联方法更新关联置信度并进行目标参数融合求精,最后通过模拟仿真验证该方法的有效性,可获得高可靠的有源无源数据融合结果。
In order to solve the problem of difficulty in fusion according to the asynchronous and different dimension measurements of active and passive data, the data fusion method between active and passive based on space-time character association is proposed. Firstly, the constitution of target track model and time model are introduced. Secondly, the single frame association method in space based on fuzzy clustering is used to calculate the association confidence, and the multi-frame association method in time based on D-S evidence theory is adopted to update the association confidence, and the target parameters are calculated more precisely. Lastly, the simulations show the proposed method works effectively, and can acquire high reliable results in active and passive data fusion.
作者
刘田
张清
LIU Tian;ZHANG Qing(Science and Technology on Electronic Information Control Laboratory,Chengdu 610036,China)
出处
《电子信息对抗技术》
2020年第2期12-16,共5页
Electronic Information Warfare Technology
关键词
特征关联
数据融合
模糊聚类
D-S证据理论
关联置信度
character association
data fusion
fuzzy clustering
D-S evidence theory
association confidence
