5 June 2018 Assessing multisensor radiofrequency-based through-the-wall mapping systemic parameters using a finite-element method framework
Rafael Saraiva Campos, Lisandro Lovisolo, Marcello Luiz R. de Campos
Author Affiliations +
Abstract
Radiofrequency (RF) through-the-wall mapping (TWM) employs techniques originally applied in x-ray computerized tomographic imaging to map obstacles behind walls. It aims to provide valuable information for rescuing efforts in damaged buildings, as well as for military operations in urban scenarios. This work defines a finite-element method (FEM) based framework to allow fast and accurate simulations of the reconstruction of floor blueprints, using very high-frequency signals. To the best of our knowledge, this is the first use of FEM in a TWM scenario. This framework allows quick evaluation of different algorithms without the need to assemble a full test setup, which might not be available due to budgetary and time constraints. Using this, the present work evaluates a collection of reconstruction methods under a parallel-beam acquisition geometry for different spatial sampling rates, number of projections, antenna gains, and operational frequencies. This work also proposes a multisensor circular acquisition geometry, which is expected to reduce acquisition time and thus enable the detection of floor layout changes (e.g., the opening and closing of a door). Considering all the drawbacks associated with such a complex problem, a robust and reliable computational setup based on a flexible method, such as FEM, can be very useful.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2018/$25.00 © 2018 SPIE
Rafael Saraiva Campos, Lisandro Lovisolo, and Marcello Luiz R. de Campos "Assessing multisensor radiofrequency-based through-the-wall mapping systemic parameters using a finite-element method framework," Journal of Applied Remote Sensing 12(2), 026025 (5 June 2018). https://doi.org/10.1117/1.JRS.12.026025
Received: 7 November 2017; Accepted: 15 May 2018; Published: 5 June 2018
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Cited by 2 scholarly publications.
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KEYWORDS
Finite element methods

Antennas

Sensors

Chemical elements

Reconstruction algorithms

Image quality

Receivers

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