A Novel Robust Adaptive Beamforming Method for Null Broadening and Interference Mitigation in High-Dynamic Scenarios

In high-dynamic environments, such as satellites, drones, and autonomous vehicles, the performance of traditional adaptive beamforming methods can be significantly affected by rapidly moving interference. Such interference may shift out of nulls and sometimes enter the main lobe-an issue that most existing methods struggle to handle. To overcome the challenge of static null broadening and main lobe invasion, a new adaptive beamforming algorithm is proposed through two synergistic innovations: real-time null broadening and dynamic main lobe interference suppression. By adding a time attenuation factor in the covariance matrix reconstruction and using virtual interference rotation, the algorithm achieves real-time null broadening and adapts to suppress interference effectively. Additionally, the moving-MUSIC algorithm is used to detect the main lobe interference and estimate its direction, followed by projection elimination to remove it. The simulation results show that the proposed method effectively maintains performance. In conclusion, the proposed method offers a reliable solution for interference suppression in dynamic environments, enhancing the robustness and performance of adaptive beamforming systems.