Aiming at the problem of small UAVs threatening the low-altitude field and its difficulty in recognition under complex electromagnetic environment, a signal recognition algorithm based on convolutional neural network (CNN) is proposed.The characteristics of the direct sequence spread spectrum (DSSS) signal under the application of UAVs are analyzed,and the signal time-frequency characteristics are obtained by short-time Fourier transform (STFT).The energy threshold noise reduction method proposed is used to reduce the noise in the time-frequency features.The CNN is designed for classification and recognition.Simulation results show that the algorithm has strong robustness and low signal-to-noise ratio environmental adaptability,and its performance is significantly better than traditional algorithms.When the signal-to-noise ratio (SNR) is -6 dB,the recognition rate reaches 0.97.