Radar Deception Jamming Identification Based on Multi-dimensional Feature Extraction

With the advancement of electronic technology, Digital Radio Frequency Memory (DRFM) jammers are capable of generating highly realistic active deception jamming signals that closely mimic radar transmission signals, severely disrupting our radar systems' ability to track real targets. To address this issue, this paper analyzes the differences in scattering point angle characteristics and polarization characteristics between target echoes and deception jamming. We propose a radar deception jamming identification method based on multi-dimensional feature extraction. This method calculates and analyzes features from multiple sets of measured radar data, obtaining jamming clustering thresholds for each feature. Based on these thresholds, we can distinguish between the jamming and the target The method maintains excellent recognition performance even under low jamming-to-noise ratios (JNR). Experimental results demonstrate the effectiveness of our proposed method.