Neural Network-Guided Sparse Recovery for Interrupted-Sampling Repeater Jamming Suppression

Zijian Wang,Jiamu Li,Yunhua Luo,Wenbo Yu,Zhongjun Yu,Hervé Aubert

doi:10.1155/2021/5368600

Abstract

Interrupted-sampling repeater jamming (ISRJ) is a new type of DRFM-based jamming designed for linear frequency modulation (LFM) signals. By intercepting the radar signal slice and retransmitting it many times, ISRJ can obtain radar coherent processing gain so that multiple false target groups can be formed after pulse compression (PC). According to the distribution characteristic of the echo signal and the coherence of ISRJ to radar signal, a new method for ISRJ suppression is proposed in this study. In this method, the position of the real target is determined using a gated recurrent unit neural network (GRU-Net), and the real target can be, therefore, reconstructed by adaptive filtering in the sparse representation of the echo signal based on the target locating result. The reconstruction result contains only the real target, and the false target groups formed by ISRJ are suppressed completely. The target locating accuracy of the proposed GRU-Net can reach 92.75%. Simulations have proved the effectiveness of the proposed method.

Highlights

Linear frequency modulation (LFM) signal is widely used in wideband radar systems for its large time-bandwidth product and high Doppler tolerance [1, 2]
Based on the distribution characteristic of the echo signal and the coherence of Interrupted-sampling repeater jamming (ISRJ) with respect to the radar signal, an ISRJ suppression method using sparse representation and deep learning target locating is innovatively proposed in this study
The TF domain data of the echo signal after pulse compression (PC) are input into the proposed gated recurrent unit neural network (GRU-Net), and the location of the real target can be acquired according to the different TF distribution characteristics and the correlation information between the false target groups formed by ISRJ and the real target. en, the coherence of the target signal and ISRJ relative to the constructed dictionary is used to sparsely represent the received echo signal

Summary

Introduction

Linear frequency modulation (LFM) signal is widely used in wideband radar systems for its large time-bandwidth product and high Doppler tolerance [1, 2]. In terms of signal processing, for dechirping radar, a band-pass filter is designed [14] by using the discontinuity characteristic of ISRJ in the time-frequency (TF) domain. This method damages the continuity of the target signal in the frequency domain, resulting in strong sidelobe components of the PC result. In terms of radar jamming suppression, due to the wide variety of radar signals and jamming models, how to make better use of deep learning methods has become the focus of research studies of scholars.

Principle of ISRJ

The Proposed Method

Simulations

Conclusions