关键词: 证据理论, 不确定因子, 分配法则, 信息融合

Abstract: In order to solve the problem that the Dempster-Shafer Theory（DST） and Dezert-Smarandache Theory（DSmT） both cannot deal with the uncertain information，this paper defines the uncertainty mass in the discernment frame.Before deeply analyzing the Proportional Conflict Redistribution rules（PCR） under the DSmT framework，the PCR2-based Adaptive Universal Proportional Redistribution rule（AUPR） is introduced.And then according to the mathematical model of the sonar，a new group of general basic belief assignment functions（gbbaf） are constructed to deal with the uncertain and imprecise，sometimes even high conflicting information obtained by sonar sensors.At last，the Pioneer 2-DXe mobile robot is used to build the belief distribution map of the environment.The experimental results adequately verify the validity and the practicability of the method proposed in this paper.It supplies a powerful theoretic evidence for dealing with the uncertain information in data fusion theory.

Key words: Dezert-Smarandache Theory（DSmT）, uncertainty mass, redistribution rule, information fusion