基于D-S证据理论的目标识别融合应用

基于D-S证据理论的目标识别融合系统,可以充分发挥多传感器信息的优势,提高目标识别结果的准确性.本文结合工程实践,分析地面目标融合识别过程中经典D-S证据理论方法处理数据出现的问题,发现使用D-S证据理论对于高冲突证据融合结果准确性较低.因此提出一种基于D-S证据理论的改进数据融合方法,将冲突因子与支持度标准偏差的相反数相乘,再与所有证据和乘积的正交相加,然后减去证据的基本概率的最大差.如果证据的冲突越大,这种方法的优势就越明显.如果证据中不存在冲突,则融合结果与原始D-S证据理论的项目一致.实验的比较数据表明,改进的信息融合方法对于改进解决冲突问题必不可少,并且是有效的.

Application of Target Recognition Fusion Based on D-S Evidence Theory

The target recognition fusion system based on D-S evidence theory can give full play to the advantages of multi-sensor in formation and improve the accuracy of target recognition results.This paper combines engineering practice to analyze the problems of classical D-S evidence theory in the process of ground target fusion recognition.It is found that the use of D-S evidence theory is less accurate for high-conflict evidence fusion results.Therefore,an improved data fusion method based on DS evidence theory is proposed.The conflict factor is multiplied by the inverse of the standard deviation of support,and then added to the orthogonality of all evidence and products,and then the maximum difference of the basic probability of the evidence is subtracted.The greater the conflict of evidence,the more obvious the advantages of this approach.If there is no conflict in the evidence,the fusion results are consistent with the items of the original D-S evidence theory.The experimental comparison data show that the improved infor mation fusion method is indispensable and effective for improving conflict resolution.