Compound radar jamming recognition based on signal source separation

To deal with various jamming signals based on digital radio frequency memories, a compound jamming signal recognition method based on source signal separation is proposed. In order to overcome label limitation of the supervised learning method in the recognition process, this paper puts forward "Separation + Recognition" strategy. Firstly, the received signals of multiple channels are preprocessed, and the number of signal sources is analyzed through the single-source detection algorithm. Then the received compound jamming signals are processed by source separation, and the independent single jamming signals can be obtained. On this basis, a fast signal compensation algorithm is added to compensate different source signals at overlapping time-frequency points, which effectively increases the integrity of the separated signals. The separated jamming signals are then put into the convolutional neural network for recognition, and the specific jamming types in the compound jamming signals can be obtained. It has been proved that the recognition accuracy of five kinds of compound jamming exceeds 90% when the jamming-to-noise ratio is 0 dB.