DSlT:面向传感网信息融合的证据推理方法

DSlT:An Evidence Reasoning Method for Information Fusion in Wireless Sensor Networks

无线传感器网络信息融合技术是近期的研究热点和难点,其面临的主要挑战包括:对高冲突信息的处理以及算法轻量级的要求.从降低计算量和处理冲突信息2方面考虑,提出一种基于逻辑表达的证据推理方法 DSlT.通过对信息的逻辑表达保留了信息中的冲突部分,提出基于逻辑运算的证据组合规则,能较好地适应高冲突证据间的融合;通过定义新的焦元,有效地减少了焦元组合数目,从而大大降低了计算量.采用算例分析和真实场景实验2种方法分别对DSlT推理方法进行验证:算例分析表明DSlT能显著提升高冲突信息融合性能,同时在执行3维证据融合运行时间对比中,DSlT比DSmT减少了81.08%;在以图像传感器网络交通信息采集为背景的真实场景实验中,通过将本方法与DST,DSmT等典型融合方法进行比较,进一步表明了该方法的有效性和先进性,也展示出该方法在无线传感器网络信息融合领域的较大应用潜力.

Information fusion in wireless sensor networks has recently been a focal point of research , meanwhile with many research challenges . The major challenges include the problem of high conflicting information fusion processing and the requirement for light‐weight algorithms with low computational complexity .In the paper ,an evidence reasoning method based on the logic expression , namely DSlT ,is proposed .By definition of the new combination rule of evidence based on the logic operation and by strict reservation of local conflict ,DSlT deals with high conflicting information fusion .By defining new focal elements ,the combination amount of focal elements is lowered greatly . Accordingly ,the computation cost is reduced dramatically .To verify the performance of DSlT ,we conduct two experiments .The first example experiment shows that our approach can effectively deal with high conflicting information fusion .Additionally ,compared with DSmT ,the computation cost of DSlT is reduced by 81.08% in the process of 3‐dimensional evidence fusion . In the real scene experiment ,vehicle classification is the application background . The traffic information acquisition platform based on an image sensor netw ork is used for collecting image data of vehicles . The comparison results further indicate the efficiency and advancement of DSlT . The experiments fully reveal the potential application prospect of DSlT in the research field of information fusion in wireless sensor networks .