Abstract: The problems of strict sampling conditions and low positioning accuracy exist in the traditional photovoltaic array arc fault location method based on electromagnetic radiation (EMR) signal, accordingly, we propose a new arc fault location method based on grid fingerprint matching. Firstly, the EMR signal of the arc is acquired with a low sampling rate, and its root mean square value is extracted as the characteristic index representing the EMR intensity. Then, BP neural network (BPNN) is adopted to mine the internal relationship among irradiance, signal receiving distance and arc EMR signal intensity, and a prediction model is established. Subsequently, according to the predicted distance between the dual-antenna array output by BPNN and the arc, the area where the arc is located is preliminarily acquired by using the triangulation method. Finally, the photovoltaic module in the located area is divided into grids to generate grid fingerprint information, and the center coordinate of the grid that most matches the predicted distance and fingerprint information is taken as the final predicted coordinate of the arc occurrence position. The experiment results show that the proposed algorithm has good positioning ability and adaptability, and the average absolute error of arc fault location is 0.306 m, which is superior to the EMR attenuation model positioning method in positioning accuracy and economy.