Mean Deviation Method for Fuzzy Multi-sensor Object Recognition

Aimed at the object recognition problem in which the characteristic values of object types and observations of sensors are in the form of triangular fuzzy numbers, a new fusion method for multi-sensor data is proposed based on mean deviation. The method defines the distance matrix between all object types and unknown object. After solving the optimization problem of maximizing the mean deviations for all attributes, the weights of the attributes are obtained objectively. Thus, the result of recognition for the unknown object is given by the overall distance. The simulated example verifies the feasibility and practicability of the proposed method.