Special Issue "Real-Time Radar Imaging and Sensing"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 March 2020).

Special Issue Editors

Dr. Ilaria Catapano
E-Mail
Guest Editor
Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy, 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
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Special Issue Information

Dear Colleagues,

The necessity of continuous and real-time surveillance and situational awareness by means of radar systems is a recognized as a necessity in a large set of civilian and security applications, ranging from indoor surveillance to elder care, anti-intrusion, and search and rescue during crisis, to cite just a few examples. Another important necessity is related to the fast imaging of large investigated area domains by means of effective data processing, when the aim is to provide results in reasonable time for static environments, such as in diagnostics and monitoring related to cultural heritage, critical and civil infrastructures, public buildings, etc.

It is worth noting that the high efficacy of radar imaging approaches is key to the development of advanced data processing strategies able to perform detection and tracking of targets in electromagnetically challenging scenarios, such as through-wall, and inaccessible/hostile environments and areas to be surveilled.

The above necessities can be tackled by means of two main lines of research.

The first is the adoption of UWB radar systems exploiting not only monostatic but even MIMO configurations, where the focus is on the forward and inverse modeling of the electromagnetic scattering for the detection, localization and geometry estimation of the targets. In this way, one is also able to develop and use target detection and tracking approaches for real-time surveillance.

The second line of research is based on the use of “simple” CW radar systems, which exploit the Doppler effect. In this case, only the target detection is enabled and the related data processing requires research efforts for the development of sophisticated but effective approaches based on statistical approaches and artificial intelligence tools. In this context, there is an increasing interest in the problem of estimating the degree of occupancy of environments, which is a noteworthy information for situational awareness during ordinary and crisis scenarios.

These two lines of research have also opened the way to efforts in new fields, such as the use of non-cooperative electromagnetic sources (Wi-Fi, GPS, 5G signals) for target detection and localization, and the use of radars on UAV and drones, where there is the further difficulty of compensating for undesired deviations from an assigned trajectory as well as the oscillations/vibrations of the observational platform.

This Special Issue aims at providing an overview of recent scientific and technological advances in the fields of real-time sensing and imaging, in terms of hardware, modeling, and data processing. We invite investigators to contribute original research articles, as well as review articles, that explore these aspects.

Potential topics include, but are not limited to:

  • Development of UWB radar systems for real-time sensing and imaging;
  • Development of CW radar systems for real-time target detection and degree of occupancy estimation;
  • Forward and inverse electromagnetic modeling for real-time imaging in static scenarios;
  • Development of strategies for real-time target detection/tracking in challenging scenarios;
  • Statistical methods and artificial intelligence tools for real-time radar sensing;
  • Data processing approaches exploiting non-cooperative sources for real-time surveillance;
  • Radar on UAV for real-time sensing and imaging;
  • Integration of radar systems in surveillance systems exploiting other kinds of sensors (optical camera, infrared cameras, magnetometers, optic fiber sensors, etc.)
  • Significant examples of case studies for real-time radar imaging and sensing.

Dr. Ilaria Catapano
Dr. Francesco Soldovieri
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 papers will be 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 2400 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

  • Radars imaging
  • Target detection/tracking
  • Forward and inverse electromagnetic modelling
  • Signal processing
  • Radar systems
  • Artificial intelligence tools
  • Statistical methods

Published Papers (2 papers)

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Research

Article
Liquid Water Detection under the South Polar Layered Deposits of Mars—A Probabilistic Inversion Approach
Remote Sens. 2019, 11(20), 2445; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11202445 - 21 Oct 2019
Cited by 3 | Viewed by 1584
Abstract
Liquid water was present on the surface of Mars in the distant past; part of that water is now in the ground in the form of permafrost and heat from the molten interior of the planet could cause it to melt at depth. [...] Read more.
Liquid water was present on the surface of Mars in the distant past; part of that water is now in the ground in the form of permafrost and heat from the molten interior of the planet could cause it to melt at depth. MARSIS (Mars Advanced Radar for Subsurface and Ionosphere Sounding) has surveyed the Martian subsurface for more than fifteen years in search for evidence of such water buried at depth. Radar detection of liquid water can be stated as an inverse electromagnetic scattering problem, starting from the echo intensity collected by the antenna. In principle, the electromagnetic problem can be modelled as a normal plane wave that propagates through a three-layered medium made of air, ice and basal material, with the final goal of determining the dielectric permittivity of the basal material. In practice, however, two fundamental aspects make the inversion procedure of this apparent simple model rather challenging: (i) the impossibility to use the absolute value of the echo intensity in the inversion procedure; (ii) the impossibility to use a deterministic approach to retrieve the basal permittivity. In this paper, these issues are faced by assuming a priori information on the ice electromagnetic properties and adopting an inversion probabilistic approach. All the aspects that can affect the estimation of the basal permittivity below the Martian South polar cap are discussed and how detection of the presence of basal liquid water was done is described. Full article
(This article belongs to the Special Issue Real-Time Radar Imaging and Sensing)
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Article
The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks
Remote Sens. 2019, 11(18), 2073; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11182073 - 04 Sep 2019
Cited by 8 | Viewed by 2084
Abstract
Aggressive fungal and insect attacks have reached an alarming level, threatening a variety of tree species, such as ash and oak trees, in the United Kingdom and beyond. In this context, Ground Penetrating Radar (GPR) has proven to be an effective non-invasive tool, [...] Read more.
Aggressive fungal and insect attacks have reached an alarming level, threatening a variety of tree species, such as ash and oak trees, in the United Kingdom and beyond. In this context, Ground Penetrating Radar (GPR) has proven to be an effective non-invasive tool, capable of generating information about the inner structure of tree trunks in terms of existence, location, and geometry of defects. Nevertheless, it had been observed that the currently available and known GPR-related processing and data interpretation methods and tools are able to provide only limited information regarding the existence of defects and anomalies within the tree inner structure. In this study, we present a microwave tomographic approach for improved GPR data processing with the aim of detecting and characterising the geometry of decay and cavities in trees. The microwave tomographic approach is able to pinpoint explicitly the position of the measurement points on the tree surface and thus to consider the actual geometry of the sections beyond the classical (circular) ones. The robustness of the microwave tomographic approach with respect to noise and data uncertainty is tackled by exploiting a regularised scheme in the inversion process based on the Truncated Singular Value Decomposition (TSVD). A demonstration of the potential of the microwave tomography approach is provided for both simulated data and measurements collected in controlled conditions. First, the performance analysis was carried out by processing simulated data achieved by means of a Finite-Difference Time-Domain (FDTD) in three scenarios characterised by different geometric trunk shapes, internal trunk configurations and target dimensions. Finally, the method was validated on a real trunk by proving the viability of the proposed approach in identifying the position of cavities and decay in tree trunks. Full article
(This article belongs to the Special Issue Real-Time Radar Imaging and Sensing)
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