Delay Error Correction Method of Photonic Beamforming Array Antenna Based on Machine Learning

Photonic beamforming array antenna addresses the problem of beam squint in the traditional pure electric phase shifter. However, in practical applications, time delay errors can arise from factors such as manufacturing defects, optical fiber variations, and temperature changes. In this study, a photonic beamforming array antenna model is established. During the experiment, systematic error for the delay of each element is introduced into the array. This kind of error has a significant impact on the performance of array antenna. Based on the technology of machine learning(ML), a method for delay error correction of photonic beamforming array antenna is proposed. The results has demonstrated that the accuracy of the beam direction is significantly improved. The time delay systematic error in optical fiber delay lines are corrected, the overall performance of the photonic beamforming array antenna system is improved.