Compressed Sensing for the Detection and Positioning of Dielectric Objects Inside Metal Enclosures by Means of Microwave Measurements
Journal article, 2018

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.

Compressed sensing

convex optimization

inverse scattering

microwave measurements

positioning

detection

sparse approximation

parameter estimation

electromagnetic simulation

Author

JOHAN WINGES

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Livia Cerullo

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

VETEC AB

Thomas Rylander

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Tomas McKelvey

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Mats Viberg

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

IEEE Transactions on Microwave Theory and Techniques

0018-9480 (ISSN) 15579670 (eISSN)

Vol. 66 1 462-476 7942082

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

Latest update

3/31/2021