Deceptive Jamming Detection in Radar Systems Leveraging Quantization-Induced Features

Deceptive jamming presents significant challenges to radar systems, especially Synthetic Aperture Radar (SAR), by creating false targets to disrupt detection and imaging. Modern deceptive jammers increasingly adopt low-resolution quantization, particularly 1-bit quantization, to simplify hardware implementation and reduce complexity while still generating convincing false targets. This operation introduces odd harmonics and spectral distortions into the intercepted signals. This paper proposes two de tection schemes to mitigate deceptive jamming in radar systems: the Temporal Variations Detection (TVD) scheme for single-scatterer scenarios and the Time-Frequency Domain Detection (TFD) scheme for multi-scatterer scenarios. Both schemes leverage the unique spectral and time-frequency characteristics introduced by quantization, a feature often overlooked in prior research. For single scatterer scenarios, the TVD scheme utilizes temporal variations induced by quantization to distinguish between true echoes and a combination of true and deceptive echoes. Theoretical analyses yield closed-form expressions for key performance metrics, including the Probability of Detection (PD) and Probability of False Alarm (PFA), under both accurate and imperfect scattering coefficient estimations. For multi-scatterer scenarios, the TFD scheme combines time frequency domain analysis with feature enhancement techniques to accurately identify false targets in SAR imagery. Simulation results show that the TVD scheme achieves detection results consistent with theoretical predictions, while the TFD scheme not only reaches a block-level PD of 92.37% for stationary jammers and 100% for moving jammers but also accurately identifies decoy targets in real-scene experiments. These results demonstrate the robustness and effectiveness of the proposed methods in addressing deceptive jamming challenges in radar systems.