Robust Mainlobe Dense False Target Jamming Identification Based on 2D Sparse Recovery

Abstract

Mainlobe dense false target jamming has brought great challenges to current radar detection due to its multi-dimensional flexible modulation capability. To this end, many effective solutions have been proposed in recent years. However, the performance of most existing methods will be largely affected in strong noise environment. In actual scenarios, strong noise environments are unavoidable. To solve this problem, this paper proposes a mainlobe dense false target jamming identification method for strong noise environments based on two-dimensional (2D) sparse recovery. First, the angle and time-delay parameters of the pulse are extracted by 2D sparse recovery. Then, the jamming identification is completed using the space-time joint feature difference within a single pulse repetition interval (PRI). On this basis, we also provide a jamming reconstruction and cancellation scheme for strong jamming environments. Compared with existing methods, the proposed method achieves accurate identification and suppression of jamming within a single PRI by effectively utilizing the spatial information of the source. It exhibits excellent robustness to strong noise and jamming environments. Additionally, it has the advantage of significantly reducing computational costs, thereby increasing overall efficiency and practicality. Numerical simulation experiment results verify the effectiveness of the proposed method.