A new error model for a special class of multiport vector network analyzers (VNAs) is presented in this paper. This model can be applied to multiport network analyzers with noncomplete reflectometers, i.e., when the measurement of the incident waves at each port is not always available. The method used to compute the error coefficients proposed here is based on a compact and easy formulation. This method is an extension of the already existing general theory for complete reflectometer multiport network analyzers. Furthermore, the new error model generalizes the theory for three-sampler two-port VNAs. The proposed model has been tested against the complete reflectometer one and exhibits the same accuracy level.

A Novel Calibration Algorithm for a Special Class of Multiport Vector Network Analyzers / Ferrero, ANDREA PIERENRICO; Teppati, Valeria; Garelli, Marco; Neri, Alessandra. - In: IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. - ISSN 0018-9480. - STAMPA. - Volume 56:(2008), pp. 693-699. [10.1109/TMTT.2008.916952]

A Novel Calibration Algorithm for a Special Class of Multiport Vector Network Analyzers

FERRERO, ANDREA PIERENRICO;TEPPATI, VALERIA;GARELLI, MARCO;NERI, ALESSANDRA
2008

Abstract

A new error model for a special class of multiport vector network analyzers (VNAs) is presented in this paper. This model can be applied to multiport network analyzers with noncomplete reflectometers, i.e., when the measurement of the incident waves at each port is not always available. The method used to compute the error coefficients proposed here is based on a compact and easy formulation. This method is an extension of the already existing general theory for complete reflectometer multiport network analyzers. Furthermore, the new error model generalizes the theory for three-sampler two-port VNAs. The proposed model has been tested against the complete reflectometer one and exhibits the same accuracy level.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/1812832
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