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Abstract-An inverse equivalent surface current method working with equivalent electric and/or magnetic surface current densities on appropriately chosen Huygens surfaces is investigated. The considered model with triangular surface meshes is compatible with the models known from method of moments (MoM) solutions of surface integral equations. Divergence conforming current basis functions of order 0.5 and of order 1.5 are considered, where the order 0.5 functions are the well-known Rao-Wilton-Glisson basis functions. Known near-field samples typically obtained from measurements are mapped on the unknown equivalent surface current densities utilizing the radiation integrals of the currents as forward operator, where the measurement probe influence is formulated in a MoM like weighting integral. The evaluation of the forward operator is accelerated by adaptation of the multilevel fast multipole method (MLFMM) to the inverse formulation, where the MLFMM representation is the key to full probe correction by employing only the far-field patterns of the measurement probe antennas. The resulting fully probe corrected algorithm is very flexible and efficient, where it is found that the computation speed is mostly dependent on the MLFMM configuration of the problem and not that much on the particular equivalent current expansion as long as the expansion is able to represent the currents sufficiently well. Inverse current and far-field pattern results are shown for a variety of problems, where near-field samples obtained from simulations as well as from realistic measurements are considered.

An adaptive approach for optimized sampling in cylindrical and spherical near-fi eld antenna measurements is described. The presented technique applies higher sampling density in rapidly varying near-fi eld regions, and skips data points in the smoother regions. Abrupt changes in the near fi eld are detected by comparing the extrapolated and the measured near-fi eld values at coarser sampling points during the measurements. A decision function, based on the signal-to-noise ratio of the measured value, is used to determine the threshold difference between the extrapolated and the measured near-fi eld values for skipping the sampling point. The reduced near-fi eld data collected is processed using the fast irregular antenna fi eld transformation algorithm (FIAFTA). FIAFTA is computationally effi cient, and capable of handling data on irregular grids with full probe correction. Several test cases are then presented related to the applicability of the given approach. A signifi cant reduction in the number of measurement points was observed, thereby reducing measurement time and the computational effort.