Compressed Sensing for the Detection and Positioning of Dielectric Objects Inside Metal Enclosures by Means of Microwave Measurements
Journal article, 2017

Based on compressed sensing and microwave measurements, we present a procedure for the detection and positioning of dielectric objects inside a metal enclosure, where the number of objects is unknown but assumed to be limited. The formulation features a convex quadratic optimization problem with 1-norm regularization, which allows for rapid detection and positioning given a precomputed dictionary. The dictionary consists of the scattering parameters computed from a single scattering object placed at the grid points of a structured grid that covers the entire measurement region. We test our method experimentally in a microwave measurement system that features a measurement region with a diameter of 11.6 cm. The measurement region is encircled by six aperture antennas, where each aperture is the end-opening of a rectangular waveguide operated from 2.7 to 4.2 GHz. We use acrylic-glass cylinders of radius 5.2 mm as scatterers and find that the compressed sensing method can correctly detect at least up to five scatterers with an average positioning accuracy of 3 mm. In addition, we investigate the performance of the method with respect to scarcity of data, where we omit scattering parameters or frequency points.

Microwave measurement

Permittivity measurement

Metals

Scattering

Dielectrics

Compressed sensing

Author

JOHAN WINGES

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Livia Cerullo

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Thomas Rylander

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Tomas McKelvey

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Mats Viberg

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

IEEE Transactions on Microwave Theory and Techniques

0018-9480 (ISSN)

Vol. PP 99 1-15

Subject Categories

Computational Mathematics

Electrical Engineering, Electronic Engineering, Information Engineering

Signal Processing

Roots

Basic sciences

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1109/TMTT.2017.2708109

More information

Created

10/8/2017