information-fusion-algorithm

说明：  本文利用模糊理论中的高斯隶属 度函数来获得模糊观测下具有概率特性的似然函数，并且由此似然函数得到每个传感器提供信息的可信度；再将各传感器的可 信度转化成基本概率赋值函数即mass 函数；最后利用证据理论对多传感器信息进行融合。对目标识别的仿真试验表明该方法获 得的结果比直接结果具有更高的精度和可靠性。(The method uses fuzzy theory in the Gaussian fuzzy membership function to obtain a probable characteristic under observation likelihood function，and the resulting likelihood function gets the credibility of the information provided by the sensors.Then the reliability of each sensor is changed to a mass function.Finally，multi-sensor information is combined by using evidence theory.Simulation of target recognition shows that the results obtained have higher accuracy and reliability.)

利用模糊推理的证据理论信息融合算法.pdf,1490979,2011-03-05