Mainlobe Deceptive Jamming Discrimination Using Distributed MIMO-FDA Radar

Multiple-Input Multiple-Output Frequency Diverse Array(MIMO-FDA) allows the suppression of signals from undesired range-azimuth regions, positioning it as a promising approach for mitigating mainlobe deceptive jamming that traditional phased-array (PA) find challenging to address. However, distinguishing real targets from false ones, especially when confronted with deceptive signals generated by modern Digital Radio Frequency Memory (DRFM) jammers, remains a significant challenge for MIMO-FDA systems due to the difficulty of signal feature-based discrimination. To address this, we introduce a strategy for differentiating between real and false mainlobe target signals using a dual-node distributed MIMO-FDA(DD-MIMO-FDA) radar system. This method leveraging the mismatch between the observed Capon spectra of the received signals and their theoretical counterparts. Simulation results demonstrate that the proposed method achieves correct discrimination probability exceeding 99% for both true and false target when SNR/INR greater than $ 7\text{dB}$. The impact of system configurations on correct discrimination rate for false target is also simulated.