Considering traditional DS evidence theory deficiencies existing in dealing with conflict evidence, the information entropy attribute is put forward based on the similarity between each evidences, which fixed the evidence classification properties. Combining the similarity attribute between each evidences, the evidence set could be divided into high credibility evidence, general evidence and conflict evidence. The sorted evidence set is given different importance coefficients, and is modified to improve. After modifying, the general evidence and high conflict evidence are closed to the high credibility of evidence opinions. Finally, DS combination rule is utilized to synthesis for the modified evidence. It is difficult for obtaining data by multiple sensors to establish the basic probability distribution function for the evidence. For the problem, making full use of the ability that rough set theory can deal with incomplete information and knowledge, the decision information table is obtained via the attribute reduction of rough set. The function values are assigned for the basic probability by the decision information table. Combining the rough set and the improved D-S evidence theory, the real data sets are measured by all kinds of sensors. The experimental results show that the improved method can not only effectively solve the conflict problem, but also reduce the uncertainty of evidence.