基于熵特征的DRFM有源欺骗干扰CFAR检测

基于数字射频存储(digital radio frequency memory, DRFM)技术的转发式干扰的存在性检测是对抗有源欺骗干扰的前提。干扰机的相位取样量化会导致干扰信号有谐波分量的寄生。在雷达距离/速度波门内同时存在目标信号和欺骗干扰信号的情形下,利用经验模态分解(empirical model decomposition, EMD)算法分离出干扰信号谐波分量,通过提取干扰谐波分量与目标回波在时频域上能量分布特征差异,提出了一种基于时频域熵特征的有源欺骗干扰检测方法。该方法不需要估计噪声参数,且具有恒虚警(constant false-alarm rate,CFAR)特性。蒙特卡罗仿真结果验证了该方法的有效性。

CFAR detection of DRFM deception jamming based on entropy feature

The detection of presence of a deception jamming which is emitted by digital radio frequency memory (DRFM) devices is the foundation of countering the active deception jammer. The phase-quantized jamming signal presents evenly spaced harmonics, compared with the input radar signal. For detecting DRFM deception jamming when both target echo and the jamming are co-existent in a range/velocity gate, the harmonics are extracted through the empirical mode decomposition (EMD) algorithm, and the energy distribution diversity in the time-frequency domain between the jamming harmonics and the target echo is analyzed, then a novel jamming detection approach is outlined based on the entropy feature. The proposed approach does not need to estimate the noise parameter, and has the precious property of a constant false alarm rate (CFAR). The validity of the proposed method is evaluated by using experimental data via Monte Carlo simulation.