An automatic harmonic selection scheme for measurements and calibration with the nonlinear vectorial network analyzer

This paper presents a method to automatically select the significant harmonics in spectra measured with the nonlinear vectorial network analyzer (NVNA). This stochastic selection criterion which is based on the t(2) -distribution, allows saving and calibrating all of the significant spectral components, without the need for wild guessing of the number of signal- containing harmonics in the measured data. To enhance the sensitivity of the algorithm, a combined selection method is proposed. The usefulness of the method is proven on amplifier measurements performed by an NVNA.