基于改进自适应加权的多传感器信息数据融合方法

Multi-Sensor Information Data Fusion Method Based on Improved Adaptive Weighting

多传感器采集的数据在数据特征和数据形式上存在较大差异,导致当前融合方法在加权过程中很难确定权值,融合效果差。文章提出一种基于改进自适应加权的多传感器信息数据融合方法,首先,进行多传感器信息数据的采集与预处理;其次,初始化每个传感器采样信息的权重;然后,根据调整后的权重对每个传感器的数据进行加权融合系数的自适应调整;最后,通过数据集合中同属性信息的聚类,实现对数据信息的融合处理。试验结果表明,所设计方法的实际应用效果更好,按照规范使用该方法进行多传感器信息数据融合,能够达到最优融合状态。

The data collected by multi-sensor has great differences in data characteristics and data forms,which makes it difficult to determine the weight of the current fusion method in the process of weighting,and the fusion effect is poor.A multi-sensor information data fusion method based on improved adaptive weighting is proposed.Firstly,the multi-sensor information data is collected and preprocessed;Secondly,initialize the weight of each sensor's sampling information;Then,according to the adjusted weight,the weighted fusion coefficient of each sensor's data is adaptively adjusted;Finally,through the clustering of the same attribute information in the data set,the data information fusion processing is realized.The experimental results show that the practical application effect of the design method in the paper is better,and the multi-sensor information data fusion using the method according to the specification can achieve the optimal fusion state.