一种在线迭代聚类的多传感器一致性数据融合方法

An Online Iterative Clustering Method for Multi Sensor Consistent Data Fusion

为了提高多传感器一致性数据融合的效果,在进行多传感器测量数据融之前,必须要对各传感器的测量数据是否具有一致性进行判定处理;针对现有各种多传感器一致性数据融合方法存在的不足,文章运用统计学中的假设检验理论、聚类分析和正态分布的优良性质,提出了一种在线迭代聚类的多传感器一致性数据融合方法,用Matlab进行大量仿真实验的结果表明,文章给出方法优于现有的多传感器一致性数据融合方法。

In order to improve the effect of multi-sensor consistent data fusion,before multi-sensor measurement data fusion,it is necessary to determine whether the measurement data of each sensor is consistent or not.In view of the shortcomings of the existing multi-sensor consistency data fusion methods,this paper proposes an online iterative clustering multi-sensor consistency data fusion method based on the hypothesis test theory,clustering analysis and normal distribution.A large number of simulation experiments with Matlab show that the proposed method is better than the existing multi-sensor consistent data fusion method.