基于期望值的模糊多传感器信息融合方法

Fuzzy multi-sensor information fusion method based on expected value

通针对目标类型的特征指标值和传感器的测量值均为三角模糊数的多传感器类型识别问题,提出了一种新的融合方法。该方法将三角模糊数决策矩阵元素转换为期望值,通过求解目标类型与未知目标属性偏差最小的优化问题得到属性的权重,根据各目标类型的综合属性期望值给出目标识别结果。较好地避免了属性权重选取的主观性,计算简单,易于计算机上实现,仿真实例表明了方法的有效性和实用性。

Aimed at the type recognition problem in which the characteristic values of object types and measurement of sensors are in the form of triangular fuzzy numbers, a new fusion method is proposed. The method transforms the triangular fuzzy number elements of decision matrix into the expected Value elements. After solving the single object programming of minimizing the total deviation between the object types and the unknown object, the weights of the attributes are obtained. The result of recognition for the unknown object is given by the comprehensive attribute expected values. This method can avoid the objectivity of selecting attributes weights. It is straightforward and can be performed on computer easily. A simulated example is given to demonstrate the feasibility and practicability of the proposed method.