Interrupted Sampling Repeater Jamming Recognition and Suppression Method Based on DBSCAN Algorithm

The interrupted sampling repeater jamming (ISRJ) is a type of coherent jamming that can not only improve the detection threshold of adjacent range cells but also induce the radar system to track a false target. In order to suppress ISRJ, we have developed an interference identification and suppression method based on a clustering algorithm. First, we obtain the time-frequency (TF) domain matrix by applying the short-time Fourier transform (STFT) to the received signal containing the target echo and ISRJ. Then, the time-frequency domain matrix is subjected to threshold decision to obtain a series of over-threshold points which are then processed by the density-based spatial clustering of applications with noise (DBSCAN) algorithm to form a series of clusters. By analyzing the number of points of these clusters, we can identify whether the cluster corresponds to the target echo or ISRJ. Recognition mainly depends on the number of cluster points and the corresponding point threshold allowing for good recognition without the need for accurate estimation of ISRJ parameters. An accurate time-frequency domain filter is constructed based on the recognition results to avoid damaging the spectral structure of the target echo while suppressing the interference. We simulate the method and verify the effect of different combinations of input signal to noise ratio (SNR) and input signal to jamming ratio (SJR) on the performance of the method through Monte Carlo simulation. The simulation results demonstrate that this method has a good suppression effect for the three ISRJ modes under various combinations of SNR and SJR.