Intelligent Detection and Separation of Radar Time-Frequency Aliasing Multi-signal Based on DeepLabV3 and GAN

‍ ‍In view of the current research on intelligent detection of radar signals， there are still some problems that have not been resolved，such as the limitation on the number of the signals， the rarity of modulation types and the inconvenience for subsequent processing， this paper proposes a radar time-frequency aliasing multi-signal intelligent detection and separation method based on DeepLabV3 and GAN. First， the time-domain data of the received signal is transformed to obtain the two-dimensional time-frequency data， and DeepLabV3 is used to detect the time-frequency data of multiple signals and realize the signal separation. For the overlapping part of the signal， this paper use GAN to perform the reconstruction of time-domain signal. Results of the experiment show that the mean intersection over union （mIoU） of the detection can reach more than 85% when the SNR is -3 dB， and the correlation coefficient between the separated signal and the original signal is higher than 0.85 when the SNR is 6 dB.