基于证据理论和Vague集的目标识别研究

Target Recognition Study Based on Evidence Theory and Vague Set

提出了一种基于D-S证据理论和区间Vague集合的多传感器数据融合算法。D-S证据理论是一种灵活处理不确定和不完全信息的数学方法;而Vague集采用区间测度,可以同时表达对目标支持和反对两方面的信息;而且允许检测信息存在一定的不确定性。将D-S证据理论和Vague集结合,提出一种多传感器数据融合方法。仿真结果表明方法具有可行性,并具有处理目标检测信息不确定性的特点。

This paper proposed a multi-sensor data fusion method based on D-S Evidence Theory and Interval-vague Vague Set。 D-S Evidence Theory is a flexible method of processing uncertain and incomplete information. Vague set is able to express both support and opposition information of the target and allow some uncertainty to some level based on the use of interval measure. The method proposed in this paper proposed a new multi-sensor data fusion method by combining the D-S Evidence Theory with Vague Set. The simulation results showed that the method is feasible and able to process the uncertainty of the detective information.