Research On Beamforming Algorithm Of Virtual Array Antenna

Beamforming determines the orientation of array sensors and plays an important role in array antennas.When the number of array elements is minimal,however,the standard beamforming algorithm's performance is restricted by the antenna's degree of freedom.Array virtual expansion technology helps improve array flexibility.As a result,the research investigates the beamforming technique using the virtual array antenna,and the main contents are outlined below:(1)Aiming at the problems of shallow zero notch and high sidelobe caused by transformation error in the interpolation virtual array beamforming algorithm,a beamforming method based on the equilibrium optimizer(EO)to optimize diagonal loading is proposed to suppress small eigenvalues disturbance caused by transformation error.The equilibrium optimizer is used to determine an optimal diagonal load under certain conditions to solve the problem that the load is difficult to determine.Simulation results showed that the beam performance of the interpolated virtual array can be improved effectively with the optimized diagonal load.(2)Aiming at the high sidelobe of traditional conjugate virtual array beamforming algorithm,a beamforming algorithm is proposed to suppress sidelobe level through array sparse optimization.In this paper,archimedes optimization algorithm(AOA)is used to optimize the location coordinate of grid points directly,which avoids the limitation of genetic algorithm.Simulation results showed that the optimized virtual array has better beam performance and lower sidelobe level.(3)A virtual array beamforming algorithm based on compressed sensing(CS)is proposed to solve the problem that the beamforming performance of traditional beamforming algorithm is insufficient due to the expected signal contained in the received data.The Chimp optimization algorithm(Ch OA)was used to improve the recovery accuracy of the orthogonal matching pursuit(OMP)algorithm under low signal to noise ratio conditions.The simulation results demonstrated that the method performs well in beamforming even with fewer snapshots.