remotesensing-logo

Journal Browser

Journal Browser

Microwave Tomography: Advancements and Applications

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 3317

Special Issue Editors

Institute for Electromagnetic Sensing of the Environment (IREA), National Research Council of Italy (CNR), Napoli, Italy
Interests: ocean monitoring; radar imaging; surface waves; ocean engineering; inverse problems; coastal bathymetry; microwave tomography
Special Issues, Collections and Topics in MDPI journals
School of Computing and Engineering, University of West London, London, UK
Interests: ground penetrating radar; remote sensing; signal processing; data processing; numerical simulations; civil engineering; forestry engineering; highway engineering; pavement engineering; construction materials
Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy (IREA CNR), Via Diocleziano 328, 80127 Napoli, Italy
Interests: signal processing; non-invasive electromagnetic diagnostics; airborne and in situ radar imaging; reconstruction of geometrical and electromagnetic features of targets by means of microwave and terahertz devices; development of data processing strategies and methodologies; image interpretation; non-invasive subsurface radar surveys of cultural heritage assets
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Microwave tomography (MWT) is a broad research field, wherein the ability of microwaves to penetrate opaque dielectric materials is exploited to perform non-invasive surveys devoted to characterizing the surface and interior of an investigated scenario. Therefore, MWT covers challenges related to the design of sensors/exposures systems and the development of imaging strategies, that can account for complex scenarios and/or be optimized for a certain application. This Special Issue deals with methodological and technological advancements referred to both hardware and software issues, working with signals in the frequency range from some hundred to a few thousand Hertz, and regarding in situ, close, and remote sensing. Specifically, it tackles strategies and technical solutions based on the analysis of microwave–material interactions and their suitable models. Moreover, innovations, possibly exploiting artificial intelligence and designed both for assessed applicative fields, such as subsoil or structure surveys, and innovative ones, i.e., health monitoring, industrial quality control, security, and safety, are welcome.

Dr. Giovanni Ludeno
Dr. Livia Lantini
Dr. Ilaria Catapano
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • microwave and radar imaging
  • signal processing
  • microwaves sensors
  • radar systems
  • inverse scattering
  • Artificial Intelligence (AI)

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

16 pages, 6763 KiB  
Article
Approximate Evaluation of the Resolution in Near Field Remote Sensing
by Ehsan Akbari Sekehravani and Giovanni Leone
Remote Sens. 2023, 15(14), 3593; https://doi.org/10.3390/rs15143593 - 18 Jul 2023
Cited by 1 | Viewed by 1352
Abstract
In linear inverse scattering, the performance of the imaging system is sometimes evaluated in terms of its resolution, i.e., its capability to reconstruct a point-like scatterer. However, there is still a lack of analytical studies on the achievable resolution. To address this, we [...] Read more.
In linear inverse scattering, the performance of the imaging system is sometimes evaluated in terms of its resolution, i.e., its capability to reconstruct a point-like scatterer. However, there is still a lack of analytical studies on the achievable resolution. To address this, we consider the point spread function (PSF) evaluation of the scattered near field for the single frequency and multi-view/multi-static case in homogeneous medium. Instead of numerically computing the PSF, we propose and discuss an approximate closed form under series expansions according to the angular ranges of both source and receiver location. In order to assess the effectiveness of the proposed approximation, we consider two cases including both full and limited view angles for the incident field and observation ranges. In addition, we provide a localization application to show the usefulness of the theoretical discussion. Numerical results confirmed the analytical investigations. Full article
(This article belongs to the Special Issue Microwave Tomography: Advancements and Applications)
Show Figures

Figure 1

17 pages, 6742 KiB  
Article
An Insight into the Warping Spatial Sampling Method in Subsurface Radar Imaging and Its Experimental Validation
by Maria Antonia Maisto, Chandan Bhat and Raffaele Solimene
Remote Sens. 2023, 15(12), 3012; https://doi.org/10.3390/rs15123012 - 08 Jun 2023
Cited by 1 | Viewed by 823
Abstract
In this paper, we are concerned with microwave subsurface imaging achieved by inverting the linearized scattering operator arising from the Born approximation. In particular, we consider the important question of reducing the required data to achieve imaging. This can help to reduce the [...] Read more.
In this paper, we are concerned with microwave subsurface imaging achieved by inverting the linearized scattering operator arising from the Born approximation. In particular, we consider the important question of reducing the required data to achieve imaging. This can help to reduce the radar system’s cost and complexity and mitigate the imaging algorithm’s computational burden and the needed storage resources. To cope with these issues, in the framework of a multi-monostatic/multi-frequency configuration, we introduce a new spatial sampling scheme, named the warping method, that allows for a significant reduction in spatial measurements compared to other literature approaches. The basic idea is to introduce some variable transformations that “warp” the measurement space so that the reconstruction point-spread function obtained by adjoint inversion is recast as a Fourier-like transformation, which provides insights into how to achieve the sampling. In our previous contributions, we focused on presenting and checking the theoretical background with simple numerical examples. In this contribution, we briefly review the key components of the warping method and present its experimental validation by considering a realistic subsurface scattering scenario for the case of a buried water pipe. Essentially, we show that the latter succeeds in reducing the number of data compared to other approaches in the literature, without significantly affecting the reconstruction results. Full article
(This article belongs to the Special Issue Microwave Tomography: Advancements and Applications)
Show Figures

Figure 1

Back to TopTop