With the increasing demand for indoor positioning, ultra wide band (UWB) technology with good communication functions and positioning performance plays an important role in the field of indoor positioning. In view of the problem that UWB communication signals are susceptible to interference in indoor complex environment, resulting in positioning errors, this paper establishes the K-means algorithm to conduct cluster analysis of the collected data, eliminates the wrong ranging values generated when there is signal interference, and improves on the basis of the classic Chan algorithm to create a Chan-IDW model to determine the actual coordinates of the target location, and then measures the accuracy of the positioning model by mean squared error (RMSE). The experimental results calculated that the average error of the two-dimensional coordinates of the target located under signal interference was 5.67 cm, and the average error of the three-dimensional coordinates was 11.34 cm, and the error was in the centimeter level, indicating that the coordinates of the target solved by the model were very close to the real coordinates. Therefore, it is concluded that the Chan-IDW model can effectively solve the problem of accurate UWB positioning under indoor signal interference.