基于Dempster-Shafer证据理论的数据融合技术研究

系统地研究了Dempster-Shafer（D－S）证据推理的数据融合技术，分析了传感器基本概率分配函数（basic probability assignment-BPA)的构造方法，分别对双传感器随参数分布的几种情况进行了检测融合，利用红外场景生成器生成的3－5μm和8－12μm双通道的红外背景及目标的序列图像，仿真了融合对探测操作特性（receiver operating character-ROC)曲线的性能改进，对AGEMA THV900型双通道红外热像仪的小目标图像也开展了实验处理，均取得了预期的结果。

Data Fusion Technique Based on Dempster-Shafer Evidence Theory

The data fusion technique of D S evidence theory is described systematically, the method of constructing basic probability assignment (BPA) of sensor is analyzed, and the dual threshold is used to divide the measurement space into confidence regions and non confidence ones. Then the Dempster's rule of combination is used to combine the belief functions of two sensors. The improvement on performance of receiver operating character (ROC) with data fusion is simulated. Double channel sequence image produced by infrared scene generator and real target sequence image of double channel imager--AGEMA THV900 are detected and fused, and the results are satisfactory.