In order to improve the intelligence level of radar emitter recognition, a new method of radar emitter modulation pattern recognition based on converted spiking neural network is proposed. The simulated radar signal is transformed into a 2D time-frequency map, and the traditional CNN (convolutional neural networks) is transformed into a SNN (spiking neuron network), which is used for radar emitter recognition. The simulation results show that the proposed method has excellent detection accuracy, and the recognition probability can reach more than 96% when the SNR is higher than -9 dB.