The complex indoor environment brings non-visual range error and multipath interference to the localization system, How to eliminate or reduce error becomes a hot spot in research to UWB indoor localization. A UWB indoor localization method based on IA-BP neural network is proposed, Which is that the error of training by BP neural network is as the antigen of calculating affinity to immune algorithm,the optimal weight and threshold of BP neural network are obtained through immune algorithm, so as to avoid the problem of slow convergence and getting into easily local optimal value of BP neural network, then get the minimum localization error. Simulation results show that the maximum error from training to 100 samples by IA-BP neural network was not more than 0.02, In the positioning scene composed of three anchors, the simulation output trajectory of the undetermined bit node was basically consistent with the actual motion trajectory.