Phased array shaped multi-beam optimization for LEO satellite communications using a genetic algorithm

LEO communications satellite antennas may require hundreds of high gain beams to achieve sufficient link margin, especially for mobile systems where the ground terminals have very low EIRP. Generally, the procedure for optimizing antenna beams for shaped coverage areas starts with a set of polygons defined in antenna angle space. These polygons are filled with synthesis stations at which the desired gain is prescribed. An optimization program is then used to synthesize the excitation of the antenna in order to achieve the desired gain at each station For multibeam coverages, if the number and size of the coverage polygons are not optimal, pattern performance will be poor. Layout is difficult at LEO because a large variation in cell size is dictated by the substantial path length variation from nadir to edge of coverage. A genetic algorithm was developed to optimize the number and size of cells for a circularly symmetric grid. Cells were then filled with synthesis stations and a least squares optimizer used to shape the antenna pattern for each cell. A phased array antenna with circular aperture and cos(1.3) theta element power pattern was used. The genetic optimizer was found to quickly produce optimal cell layouts for arbitrary altitude, field of view, and directivity requirements. It was also a very good way to quickly and accurately determine the number of beams needed for a particular set of requirements.