Multi-Sensor Fuzzy Interval Multi-Attribute Decision Fusion Method
Xia Wu · 2023
For the increasingly complex information environment and changing target characteristics, most of the existing multi-sensor information fusion methods are “static”, and less consider the influence of sensor reliability change and the timeliness of the multi-dimensional feature index weight in the measurement process on the fusion results. To solve this problem, an information fusion method based on fuzzy theory and interval multi-attribute decision making is proposed. The method defines the information quality optimization degree from the consistency of the support degree of each sensor to fuzzy proposition, uses interval number and multi-attribute decision theory to define the comprehensive confidence degree of feature recognition, and objectively determines the fusion weight of the sensor from these two aspects, and solves the reasonable evaluation of the sensor information and target feature weight when it is fuzzy and uncertain. Therefore, an intelligent optimization decision level fusion recognition model is constructed. Finally, the experiment of target recognit-ion proves that this method has good accuracy.