An Intelligent Anti-main Lobe Repeat Back Jamming Method for FDA-MIMO Radar Based on JADE Algorithm

In view of the problem that the conventional phased array radar and multiple-input multiple-output (MIMO) radar cannot effectively distinguish between target and false target when facing the same angle and different distance from the main lobe distance forwarding jamming, an intelligent anti-jamming method based on matrix joint approximate diagonalization of eigenmatrixe (JADE) blind source separation algorithm is proposed based on frequency diversity array (FDA)-MIMO radar. This method is also effective for multi mainlobe jamming scenarios. The received signal is first beamformed, and then the beam output signal is matched filtered. According to the interference of the frequency diversity sub-frequency, the undisturbed sub-frequency is adaptively selected, and the JADE algorithm is used to separate the interference from the target, so as to realize intelligent anti-interference. In order to strengthen the countermeasure effect against false target forwarding interference, low-pass narrowband filtering is used for each frequency diversity sub-frequency to filter out-of-band interference. Simulation results show that the receiving beam domain JADE algorithm based on intelligent frequency selection strategy is applied to FDA-MIMO radar to achieve good mainlobe anti-jamming effect.