%0 Journal Article
%T Calibration of a Six-Port Position Sensor via Support Vector Regression
%A Hao Peng
%A Tao Yang
%A Ziqiang Yang
%J PIER    C
%D 2012
%I EMW Publishing
%R 10.2528/PIERC11101707
%X In this paper, a calibration technique for the position sensor via support vector regression (SVR) is proposed. The position sensor adopts a zero-intermediate frequency architecture based on a six-port network, which is used for directly measuring the phase differences and indirectly reflecting the position. The SVR, which implements the structural risk minimization (SRM) principle, provides a good generalization ability from size-limited data sets. The results indicate that the SVR model can achieve a great predictive ability in positioning, with an accuracy of 2.41 mm over a distance range of 274.5 mm.
%U http://www.jpier.org/pierc/pier.php?paper=11101707