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A novel design of a robust ten-port microwave reflectometer with autonomous calibration by using neural networks

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Identifiers
URI: http://hdl.handle.net/10317/1484
ISSN: 0018-9480
DOI: 10.1109/TMTT.2008.2007318
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Author
Monzó Cabrera, Juan; Pedreño Molina, Juan Luis; Toledo Moreo, Ana Belén; Lozano Guerrero, Antonio José
Research Group
Grupo de Electromagnetismo y Materia (GEM); División de Sistemas e Ingeniería electrónica (DSIE)
Knowledge Area
Teoría de la Señal y las Comunicaciones
Publication date
2008-12
Publisher
IEEE Microwave Theory and Techniques Society
Bibliographic Citation
MONZÓ CABRERA, Juan, PEDREÑO MOLINA, Juan L., LOZANO GUERRERO. Antonio, TOLEDO MOREO, Ana. A novel design of a robust ten-port microwave reflectometer with autonomous calibration by using neural networks. IEEE Transactions on Microwave Theory and Techniques, 56 (12 parte 1) : 2972 - 2978, 2008. ISSN 0018-9480
Peer review
Sí
Keywords
Ten-port
Neural network
Autonomous calibration
Reflectometer
Diez puertos
Red neuronal
Calibración autónoma
Reflectómetro
Abstract
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 measur ...
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