Sparse Array Beamforming Algorithm Research

For many radar and communication applications of scanning array antennas, extreme narrow main beamwidth is required to improve the spatial resolution. To achieve this goal, one way is to increase the element number of the array, but it will bring higher cost and more complexity with respect to the system; another way is to use sparse antenna array, whose element spacing is relatively larger thanλ/ 2, it has larger aperture without increasing the number of element, the sparse array can meet the design goal of narrow scanning beamwidth and high resolution, and the effect of mutual coupling is reduced. The sparse antenna arrays with the strong directivity have a great deal applications in aperiodic arrays. In recent years, the sparse antenna arrays are widely applied in satellite communications, high frequency groundwork phased array radar and interferometer of radio astronomy.The sparse array also has some disadvantages, for example, the sparse array has lower power than the equally spaced array with the same array aperture, to acquire high resolution, the sparse array usually has an aperture of more than 100 meters, and it will increase the complexity of the system and the difficulty to the following signal processing. For the problem of low emitted power, phase-only transmitting beamforming algorithm is needed to research to improve the efficiency of the element, and the fast adaptive beamforming algorithms are also needed to research.In this dissertation, the basic concept of sparse array is studied, the array beam patterns of sparse array and uniform array are presented, computer simulation results verify the validity of the QRD-SMI algorithm applied to sparse array, diagonal loading technique is analyzed, Neural Network applied to adaptive beamforming is studied, and a method of phase-only wide nulling based on Genetic Algorihtm is proposed, then the real-time ability is improved by combining the Neural Network.