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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Radiation center estimation from nearfield data using a direct and an iterative approach
 Antenna Measurement Techniques Association AMTA: Antenna Measurement Techniques Association Symposium (AMTA) 2017 : 1520 Oct. 2017 Piscataway, NJ: IEEE, 2017 ISBN: 9781538637630 6 S. 
 Antenna Measurement Techniques Association (AMTA Annual Meeting and Symposium) <39, 2017, Atlanta, Ga.> 

 Englisch 
 Konferenzbeitrag 
 Fraunhofer FHR () 
Abstract
Spherical NearField (SNF) measurements are an established technique for the characterization of an Antenna Under Test (AUT). The normal sampling criterion follows the Nyquist theorem, taking equiangular samples. The sampling step size depends on the smallest sphere that, centered in the coordinate system of the measurement, encloses the AUT, i.e. the global minimum sphere. In addition, a local minimum sphere can be defined as the sphere with minimum radius which, centered in the AUT, encloses it alone. The local minimum sphere is always equal or smaller than the global minimum sphere, being equal when the AUT is centered in the coordinate system of the measurement. It is implied that the center of the local minimum sphere coincides with the radiation center. In this paper, the relative position of the radiation center of an AUT with respect to the center of the coordinate system of the measurement is estimated from SNF data using two approaches. The first approach takes the phase center as an estimation of the radiation center and is based on the method of moving reference point, strictly valid for the farfield case only. The second approach is based on a spherical modes spectrum analysis, iteratively translating the Spherical Wave Expansion (SWE) until the convergence criterion is met. Both methods are applied on undersampled systems by simulation for different cases and antennas. The estimation error of both methods is compared and discussed, highlighting the convenience of each method and an application with compressed sensing techniques.