TY - JOUR 
A1 - Monzó Cabrera, Juan
AU - Pedreño Molina, Juan Luis
AU - Lozano Guerrero, Antonio José
AU - Toledo Moreo, Ana Belén
T1 - A novel design of a robust ten-port microwave reflectometer with autonomous calibration by using neural networks
Y1 - 2008
SN - 0018-9480
UR - http://hdl.handle.net/10317/857
AB - In this study, a novel ten-port waveguide microwave
sensor is designed, implemented, calibrated and tested in order
to obtain the reflection coefficient magnitude and phase. This reflectometer
is based on the well known six-port structure but the
number of detectors has been increased to eight in order to improve
the sampling procedure of the standing wave present within
the waveguide. In addition, a learning method based on neural networks’
usage has been implemented for autonomous calibration
from the data collected by a vector network analyzer. An automated
procedure consisting of a moving sample within a multimode
cavity has enabled different reflection coefficients to be obtained.
Neural networks have been employed in order to learn the
relationship between the actual reflection parameter and the acquired
signals from eight power detectors. This novel device has
been calibrated with a neural architecture based on radial basis
functions and the error of device measurements has been analyzed.
This new design and the incorporated neural network calibration
allow one to avoid problems caused by fault or nonlinearity of the
detectors, and to get robustness, flexibility and adaptability characteristics
for the presented device.
KW - Teoría de la Señal y las Comunicaciones
KW - Calibración autónoma
KW - Red neuronal
KW - Parámetros de dispersión
KW - Reflector de microondas
KW - Autonomous calibration
KW - Neural network
KW - Scattering parameter
LA - eng
PB - IEEE Microwave Theory and Techniques Society
ER -