Abstract: In real data fusion applications based on multisensor systems，the collection of the false evidence is inevitable，which may be caused by many factors such as atrocious weather or enemy’s jammer or the flaws of the sensor itself.The colleted false evidence will lead to evidence conflicting problems and greatly influence the final fusion results.In order to find the false evidence，a new method based on distance function is presented.A distance between the bodies of evidence is introduced to measure the conflict degree of each evidence.The average distance of each piece of evidence is well defined as well as the system average distance，which is used as a decision level.A piece of evidence can be regarded as false evidence if its average distance is larger than the system average distance.A numerical example in target recognition based on multisensor fusion is used to illustrate the efficiency of the proposed method.

Key words: information fusion, evidence theory, distance function, target recognition

摘要： 由于人为或是自然因素的影响，多传感器应用系统中收集的证据中常常存在伪证据。这些伪证据导致信息融合过程中出现证据冲突，并影响最后的融合结果。为了有效识别伪证据，提出一种基于距离的伪证据识别方法。定义了各个证据的平均证据距离，设定一个阈值作为系统的平均证据距离作为判断依据，当一个证据的平均证据距离高于系统的平均证据距离时，则该证据被判断为伪证据，用一个目标识别的算例表明该方法简单有效。

关键词: 信息融合, 证据理论, 距离函数, 目标识别