In order to solve the problem of high complexity and low accuracy of the current method for Volterra frequency-domain kernel identification, a method for Volterra frequency-domain kernel identification based on neural network is proposed. Firstly, the amplitude of each Volterra frequency-domain kernel is accurately measured after choosing multiple frequency components. Then, we use the characteristics of BP neural network that it can approximate nonlinear functions to design different models for different-order Volterra frequency-domain kernels, so as to identify each kernel. Finally, a nonlinear circuit is adopted for simulation. The results show that this method can directly identify all the Volterra frequency-domain kernels in the frequency range, and the process is simple with high accuracy, which is suitable for engineering realization.