Twice optimised near‐field scanning system for antenna characterisation

Abstract

The near‐field (NF) acquisition time depends on the sampling strategy and on the measurement hardware. Optimised sampling based on singular value optimisation dramatically reduces the number of measurement points and the scanning path length compared to conventional samplings, without impairing the far‐field reconstruction. Furthermore, an optimised control approach, tracking a sufficiently smooth trajectory allows better performance in terms of velocity and precision, significantly reducing the scanning time. We show that the combined use of an optimised sampling and an optimised controller drastically reduces the measurement time. The sampling strategy provides a raster grid of optimally selected rows hosting samples optimally arranged according to a row‐wise non‐uniform distribution. The optimised control drives the NF scanner and the vector network analyser to acquire the data along each row by a continuous probe movement with a variable velocity, accelerating and decelerating between two consecutive sampling points. The sparsity of the NF locations enables a significant increase in the average speed between two consecutive points. The controller is realised with a proportional‐integral‐derivative law with a compensation signal and a filter downstream. The controller does not demand complex hardware and can be realised in an extremely simple, cheap and off‐the‐shelf solution.

On the Optimal Field Sensing in Near-Field Characterization

“…Several contributions to SVO have appeared throughout the literature with a target different from the one pursued in the present paper. In [ 18 , 19 ], SVO has been used for plane-polar near-field acquisitions; in [ 20 , 21 ], it has been exploited for very-near-field measurements performed with dielectric probes; in [ 2 ], a multi-frequency extension has been given; in [ 17 ], it has been applied to a helicoidal cylindrical scanning; in [ 3 ], a criterion to determine the size of the portion of the measurement plane and the “quasi-raster” scanning have been introduced; in [ 22 ], SVO has been extended to the case of incoherent sources; in [ 23 , 24 ], it has been extended to inverse scattering, also with multi-resolution purposes; in [ 25 ], the use of gradient information in the optimization of the sample locations has been introduced; in [ 26 , 27 ], SVO has been used in connection to the design and construction of an innovative scanner controller; finally, in [ 28 , 29 ], extensions to the spherical and cylindrical scanning geometries have been provided.…”

“…The validity of SVO has been extensively experimentally verified in various scanning geometries [ 2 , 3 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. The purpose of this paper is showing the “optimality” of SVO by formulating the problem in a rigorous mathematical setting and also proving that other possible solutions, related to the representation of the measurement functionals through generalized quadrature, lead essentially to the same results.…”

Efficient Planar Near-Field Measurements for Radiation Pattern Evaluation by a Warping Strategy

“…From a general perspective, devising the sampling scheme can be addressed by a sensor selection procedure [16]. This way, the problem is phrased as the search for a finite number of measurement positions, among candidates available over a dense grid, by optimizing some metrics related to the singular values of the radiation operator [17] - [21]. Another approach takes into account the mathematical features of the Green function that suggests the field can be approximated by a band-limited function, once a suitable parametrization for the observation variables is employed and a proper demodulating exponential term is singled-out [22].…”

Near-Field Warping Sampling Scheme for Broad-Side Antenna Characterization

“…The most advanced testing procedures rely on near-field measurement techniques that consist of measuring the field radiated by the antenna under test at a relatively short range within an anechoic environment [1][2][3] and then to compute the far-field pattern from such measurements. More in detail, near-field measurements are usually collected by mechanically scanning a measurement surface [4] and then the measured data are processed by the so-called "near-field to far-field transformations" [3,[5][6][7], or related approaches [8,9], to obtain the antenna radiation pattern. For large antennas, the number of required measurements may become extremely high.…”