Robust Adaptive Beamforming Signal Techniques for Drone Surveillance

摘要

Drone surveillance poses a big technical challenge in the signal beamforming due to the drones' small size and low flying speed at low altitude collisions and etc. In a drone surveillance system, robust adaptive beamforming is required to identify suspicious targets. However, interference motion and array steering vector (ASV) mismatch problems often occurs in the situation of the antenna platform motion or propagation channel variability. To solve these problems, we propose a robust adaptive beamforming algorithms, which can broaden interference nulls. Specifically, by introducing a norm constraint, the proposed algorithm produces a broad trough at the direction of interference and adopts an idea of worst case performance optimization to robustly against the ASV mismatch. Simulation results demonstrate the validity of the proposed algorithm in terms of both output beampattern and signal-to-interference-plus-noise ratio (SINR).