The division-of-amplitude photopolarimeter (DOAP) is a sensor that can rapidly determine the polarization state of the incident light. A data processing method for the DOAP based on an artificial neural network (ANN) was presented. A multilayer feedforward neural network model was set up whose inputs are the electrical signals produced by an electronics system of the DOAP, and outputs are the Stokes parameters of the incident light. The mapping relationships between the electrical signals and the Stokes parameters can be determined by training the neural network. After the electrical signals were measured, the Stokes parameters of the incident light can be calculated via the neural network which has been trained. The total root-mean-square deviation of Stokes parameters is 1.9%.The testing results show that the data processing method based on the neural network is slightly better than that based on the matrix operation on the aspects of measuring precision.