A Compressed Sampling for Spherical Near-Field Measurements

Spherical near-field measurements are regarded as the most accurate technique for the characterization of an Antenna Under Test's (AUT) radiation. The AUT's far-field radiation characteristics can be calculated from the Spherical Mode Coefficients (SMC), or spherical wave coefficients, determined from near-field data. The disadvantage of this technique is that, for the calculation of the SMC, a whole sphere containing the AUT must be Nyquist-sampled, thus directly implying a longer measurement time when only a few cuts are of interest. Due to antennas being spatially band-limited, they can be described with a finite number of SMC. Besides, the vector containing the SMC can be proved sparse under certain circumstances, e.g. if the AUT's radiation pattern presents information redundancy, such as an electrical symmetry with respect to coordinate system of the measurement. In this paper, a novel sampling strategy is proposed and is combined with compressed-sensing techniques, such as basis pursuit solvers, to retrieve the sparse SMC. The retrieved sparse SMC are then used to obtain the AUT's far-field radiation. The resulting far-field pattern is compared for both simulated and measured data. The reduced number of points needed for the presented sampling scheme is compared with classical equiangular sampling, together with the estimated acquisition time. The proposed sampling scheme improves the acquisition time with a reasonable error.