A New Method in Wide Band Adaptive Beam Forming By Deep Learning Method In An Array System

Today, strategic UAVs with their ultra-modern facilities in the fields of COMMAND, ELINT and high-resolution imaging and their guidance and navigation and sending and receiving information at a high rate through communication links with satellites are able to collect valuable information. which can disturb the balance of the battle scene and if needed, they will be able to act and destroy the country's strategic infrastructures. Therefore, in order to deal with this type of birds, it is felt to use an electronic warfare system that is capable of active and passive tracking with the ability to disrupt. In this system, due to the many advantages of antenna array and electronic beam shaping, this method has been used. Depending on the operational needs, these arrays should be capable of receiving several Mhz instant bandwidth signal over the entire operating frequency range x and Ku. In array antennas by sending and receiving broadband signals, the narrow beamforming structure will not respond to the beamforming, so wideband beamforming structures are used. In broadband structures, due to the increase in the number of beamforming coefficients from the M coefficients to the M * J coefficients, if the common optimization algorithms in wideband beam formation are used to determine the coefficients, computational complexity and therefore power The required processing and computational latency are very high, which is one of the challenges of beamforming in wideband systems. In this paper, in order to reduce the computational complexity, the deep learning method has been used and it is shown that the proposed method reduces the complexity by determining the coefficients significant while maintaining efficiency.