Adaptive Cross Approximation Algorithm Accelerated Inverse Equivalent Current Method for Near-Field Antenna Measurement

摘要

The adaptive cross approximation (ACA) algorithm is adopted to efficiently compute the discretized forward integral equation operator in the near-field (NF)-far-field transformation process by utilizing the rank-deficient nature of the well-separated interactions between the equivalent sources and the measurement probes. The threshold of the ACA compression is carefully investigated to achieve results that are more accurate. Besides, an octree-based geometrical-adaptive grouping scheme is proposed where two different grouping strategies are designed for planar and spherical measurements, respectively. To further increase the accuracy and efficiency of the computation, the leaf-level cube size for the sources and probes are also flexibly decided, since the corresponding two spatial distribution densities vary significantly. The effectiveness of the proposed method is validated with synthetically generated NF data and with spherical measurements of a double-ridged waveguide antenna.