COMPRESSIVE SENSING TECHNIQUE FOR APERIODIC ANTENNA ARRAY DESIGN

Abstract

The aperiodic antenna array is an appreciable research work that has many advantages over the periodic antenna array. Aperiodic means “non-uniform” or “irregular”. The main difference between periodic and aperiodic antenna arrays is spacing between each element is not uniform in the aperture. This is a significant research work that started in the 1960s and continues. It will be beneficial to many applications like satellite communications, wireless communications, Navybased communications, etc. As periodic antenna arrays suffer from grating lobes, sidelobes, and costs in a high frequency larger aperture arrays, they can be easily replaced by an aperiodic antenna array which deducts the errors that occur in a periodic array. In this framework, we tried to show in a detailed situation of the periodic and aperiodic antenna array and its design techniques. The design of aperiodic antenna arrays is handled by a few optimization techniques that are Genetic algorithm, Particle swarm optimization, least squares method, compressive sensing methods, etc. In this body structure, we have considered a new technique named the Compressive sensing method which adds benefits over other techniques and is discussed in a detailed solution in section (1.4) for an aperiodic antenna array. To prove aperiodic arrays are better than periodic, two design examples are performed below in section (3). Design of planar antenna array in periodic way and aperiodic way through optimization in section (3.1) and design of Dolph Tschebyscheff antenna array was designed in periodic and aperiodic way in section (3.2). The design examples of a periodic and aperiodic array with compressive sensing approach of convex optimization with required algorithms are performed in Matlab software. Comparison of periodic and aperiodic of planar and tschebyscheff antenna array pattern are discussed below which has very drastic change in side lobes and grating lobes. Frame work concludes by idealizing the future work of an aperiodic array.