LAUSR

Unmanned aerial vehicle (UAV) has been widely used in various fields, which mainly relies on global navigation satellite system (GNSS) to obtain position information. However, fast-moving jamming poses a big challenge for UAV navigation. This motivates us to develop new robust adaptive beamforming technique that is capable of enhancing the navigation signal and suppressing the jamming efficiently. Since the navigation signal and jamming present non-Gaussianity in statistics, the minimum dispersion distortionless response (MDDR) beamformer is utilized, which exhibits better performance of non-Gaussian signal reception over the minimum variance-based beamformer. To suppress the fast-moving jamming, the minimum power constraint is added to the optimization problem regarding to the MDDR beamformer, leading to a resultant problem with a quadratic constraint. Furthermore, instead of the quadratic constraint, a linear version is derived under the power constraint to achieve a shape null sector towards the fast-moving jamming, and as a consequence, a linearly constrained MDDR beamforming is established. This allows us to develop two algorithms, i.e., quasi-MVDR algorithm and Newton's method, to accelerate the solution. Simulation results show that the proposed beamformer is able to suppress the fast-moving jamming efficiently for UAV navigation.