关键词: 证据理论, 数据融合, 模糊信息, 目标识别

Abstract: Evidence theory is widely used in automatic target recognition (ATR) system. One of the problems in real application is that not only the observation collected by sensors, but also the attributes of targets in the model database may be fuzzy too. In this situation, how to automatically determine the mass function of fuzzy information is an open issue. In this paper, a method of automatically determining mass function for target recognition is presented. After representing both the individual attribute of target in the model database and the sensor observation or report as fuzzy membership function, a random sets model of this fuzzy information is introduced. Then, a likelihood function is obtained to deal with the fuzzy data collected by each sensor. The likelihood function has probabilistic character and can be transformed into a mass function, which numerically shows the support degree of the hypotheses that the target is a certain target under the collected fuzzy information. The present approach has been tested in an ATR system to illustrate its efficiency and can be easily used in many fuzzy information fusion systems.

Key words: Evidence theory, data fusion, fuzzy information, target recognition