Spatial Multi-Interference Suppression in Monopulse Radar with Reconfigurable Distributed Array Nodes

Array radar signal processing is extensively employed in a variety of applications, including the detection of targets and the estimation of parameters for unmanned aerial vehicles (UAVs). Nonetheless, within radar systems, effectively mitigating multiple concurrent interferences, especially the mainlobe interferences (MLIs), during the estimation of target parameters remains a significant technical challenge. The objective of this research is to investigate anti-interference and high-precision angle measurement in monopulse radar for distributed array nodes (DAN) in the presence of multiple oppressive MLIs and sidelobe interferences (SLIs). Firstly, the signal model of the DAN including the target and interferences is established. Then, to make the monopulse curve consistent with the quiescent monopulse curve while suppressing MLIs and SLIs, a processing approach that the received signal is weighted by two-stage including intra-node and inter-node weighting is proposed, achieving the purpose of angle measurement. Also, the DAN in actual conditions is taken into account, such as computational and transmissive resource limitations. So, a modified framework genetic algorithm is applied for node selection to reduce the pressure on computational resources while improving the effectiveness of MLIs suppression. Finally, simulation experiments demonstrate that the proposed method performs the suppression of three MLIs and two SLIs with 8 nodes, and the nullings of all interferences in pattern are below -60 dB. In addition, the proposed method achieves angle estimation for up to three targets. Further, the performance enhancement of MLIs suppression by selecting the optimal 8 nodes out of 15 nodes is confirmed, and the nullings of all three MLIs are decreased by at least 10 dB with regard to the worst case.