Mainlobe Deception Jamming Suppression Based on DRFM Quantization Characteristics and Blind Source Separation

To address the challenge of distinguishing between mainlobe deception jamming and real target echoes in radar signals after blind source separation (BSS), this paper proposes a deception jamming suppression method based on the quantization characteristics of Digital Radio Frequency Memory (DRFM). First, the Joint Approximate Diagonalization of Eigenmatrices (JADE) algorithm is employed to separate uncorrelated components of the radar signal. Subsequently, pulse compression is applied to eliminate noise and suppression jamming signals, retaining only target echo signal and deception jamming signal. Leveraging the entropy reduction property of quantized signals, the entropy values of real target echo and deception jamming are analyzed and compared to achieve jamming suppression. Simulation results demonstrate that the proposed method effectively discriminates deception jamming from true target echoes. Particularly under high jamming quantization bit conditions, the entropy-based analysis still maintains a high correct discrimination rate.