Method based on interval number for multi-sensor information fusion

This paper aimed at the object recognition problem in which the characteristic values of object types and observations of sensors are in the form of interval numbers, a new fusion method for multi-sensor data is proposed from the viewpoint of decision making theory. The method defines the distance between the two interval numbers, obtains the distance matrix between all object types and unknown object. After solving the optimization problem of minimizing the distance between the object types and the unknown object, the weights of the attributes are obtained. Thus, the result of recognition for the unknown object is given by the overall distance. This method can avoid the subjectivity of selecting attributes weights. It is straightforward and can be performed on computer easily. Finally, a simulated example is given to demonstrate the feasibility and practicability of the proposed method.