Efficient spherical near‐field antenna measurement using CS method with sparsity estimation

Abstract

Spherical near-field antenna measurement requires the acquisition of many points, which makes the measurement process time-consuming. Since the antenna radiation pattern has a sparse representation on the basis of vector spherical harmonics, compressive sensing (CS) can be used to reduce the number of sampling points in the near-field antenna measurement. CS requires knowledge of sparsity in advance to determine the number of sampling points. The phase transition diagram is usually used to determine the number of measurements, which is again time-consuming and requires a large number of computing data. In this study, the method for sparsity level estimation is used to estimate the sparsity level of an arbitrary antenna's near field. Using this sparsity estimation method is a novel antenna measurement which has many applied advantages. As a case in point, it estimates the sparsity level of a radiation pattern with a few numbers of measurements, which makes the CS method efficient and affordable in the near-field measurement technique. To confirm the effectiveness of the proposed method, a standard horn antenna is investigated.