Aiming at the inconsistency of evidence in multi-sensor target recognition,a multi-sensor evidence fusion algorithm based on evidence belief entropy and similarity is proposed for target recognition.Firstly,a measurement model of sensor evidence uncertainty based on belief entropy is introduced by using the inconsistent uncertainty and nonspecific uncertainty of sensor evidence.On this basis,a method of generating sensor evidence weight based on confidence entropy and similarity is designed by combining the distance and conflict of sensor evidence.Finally,a multi-sensor evidence fusion model is constructed.The simulation results show that the proposed method is more effective than the traditional algorithm in target recognition.