Interrupted-Sampling Repeater Jamming-Suppression Method Based on a Multi-Stages Multi-Domains Joint Anti-Jamming Depth Network

Abstract

Jamming will seriously affect the detection ability of radar, so it is essential to suppress the jamming of radar echoes. Interrupted-sampling repeater jamming (ISRJ) based on a digital-radio-frequency-memory (DRFM) device can generate false targets at the victim radar by the interception and repeating of the radar transmission signal, which is highly correlated with the true target signal. ISRJ can achieve main lobe jamming and has both deception and oppressive jamming effects, so it is difficult for the existing methods to suppress this jamming effectively. In this paper, we propose a deep-learning-based anti-jamming network, named MSMD-net (Multi-stage Multi-domain joint anti-jamming depth network), for suppressing ISRJ main lobe jamming in the radar echo. In the first stage of MSMD-net, considering that the target signal is difficult to detect under a high jamming-to-signal ratio (JSR), we propose a preprocessing method of limiting filtering on the time-frequency domain to reduce the JSR using the auxiliary knowledge of radar. In the second stage, taking advantage of the discontinuity of the jamming in the time domain, we propose a UT-net network that combines the U-net structure and the transformer module. The UT-net performs target feature extraction and signal reconstruction in the signal time-frequency domain and preliminarily realizes the suppression of the jamming component. In the third stage, combined with phase information, a one-dimensional complex residual convolution U-net network (ResCU-net) is constructed in the time domain to realize jamming filtering and signal recovery further. The experimental results show that MSMD-net can obtain the best jamming suppression effect under different transmitted signals, different jamming modes, and different jamming parameters.

An Attention-Guided Complex-Valued Transformer for Intra-Pulse Retransmission Interference Suppression

“…Typically, previous research [34][35][36] has dealt with complex-valued signals by separating the real and imaginary parts, either by concatenating or by processing them through two channels. This approach treats the real and imaginary parts as independent, overlook-ing the inherent phase information of complex signals.…”

“…Jiang et al [34] utilized a series of auto-encoders to extract signal and RF features, followed by another auto-encoder to reconstruct radar signals. He et al [35] proposed a multi-stage multi-domain joint anti-jamming depth network to suppress ISRJ. This network integrates U-Net and transformer architectures to execute interference suppression through a series of steps, including TF filtering, feature reconstruction, and residual reconstruction.…”

Radar Anti-Jamming Decision-Making Method Based on DDPG-MADDPG Algorithm

“…In actual electromagnetic countermeasures, there are various ECCMs and jamming modes, and they are not in a one-to-one correspondence. Many ECCMs can suppress the same jamming mode, and one ECCM can also weaken multiple forms of jamming [31]. Therefore, in a complex electromagnetic environment, the scale of the radar anti-jamming knowledge base is becoming larger and larger, resulting in a large action space and a long convergence time in the optimization process of ECCMs [32].…”

PN Codes Estimation of Binary Phase Shift Keying Signal Based on Sparse Recovery for Radar Jammer

“…With the development of electronic warfare, the radar jammer has become one of the most important equipment of the modern war [ 1 ]. It senses the hostile radars and invalidates them by radioing jamming signal to them [ 2 , 3 ]. The radar jammer is able to estimate the parameters of the radar signal and generate a coherent jamming signal based on the estimated results.…”