一种复杂环境下多传感器数据融合方法

针对现有方法没有利用证据数据采集源头的可靠性信息这一问题,结合温度数据采集,提出一种复杂环境下多传感器数据融合算法。从多传感器采集的原始数据出发,通过原始数据分析当前传感器节点的信任度,对当前传感器证据进行相应的修正,从证据源层面修正冲突证据。在证据融合阶段引入支持度修正证据迭代融合思想,比较融合证据与原证据的差异冲突等属性来评估原证据的支持度并修正原证据,将修正后的证据再次融合,多次迭代至最终融合结果收敛。试验仿真与现存的多种融合方法进行比较,仿真结果验证了本研究方法在解决证据冲突问题上的有效性。

A method of multi-sensor data fusion under the complicated environment

The existing methods do not use the reliability information of the source of evidence data collection, a multi-sensor data fusion algorithm based on the temperature data in complex environment was proposed. It proceeded from the sensor data source, analyzed the evidence source information, evaluated the confidence measure, and revised the conflict evidence with the confidence measure. In the evidence fusion moment, we used iterative fusion method to revise and fusion evidence until the fusion result convergence. Compared with other fusion methods, this method was effective and had better results in the question of evidence conflict.