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Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 56389

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Prof. Moeness Amin

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Director, Center for Advanced Communications, Tolentine Hall Rm 119, Electrical and Computer Engine, 800 Lancaster Avenue, Villanova, PA 19085, USA

Dr. Stefano Perna

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1. Department of Engineering (DI), Università degli Studi di Napoli “Parthenope”, 80143 Napoli, Italy
2. Institute for Remote Sensing of Environment (IREA), National Research Council (CNR), 80124 Napoli, Italy
Interests: SAR; airborne SAR data modeling and processing; modeling of electromagnetic scattering from natural surfaces; synthesis of antenna arrays
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Dr. Francesco Soldovieri

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National Research Council of Italy (CNR), Institute for Electromagnetic Sensing of the Environment (IREA), Via Diocleziano 328, 80124 Naples, Italy
Interests: electromagnetic scattering; radar imaging; ground penetrating radar; data integration; non-invasive monitoring tools
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Microwave radar imaging plays a key role in several civilian and defense applications, such as security, surveillance, diagnostics and monitoring in civil engineering and cultural heritage, environment observation, with particular emphasis on disasters and crisis management where it is required to remotely sense the area of interest in a timely, safe and effective way. To fulfill these constraints, a technological opportunity is offered by radar systems mounted onboard smart and flexible platforms, such as ground-based ones (GBSAR), airplanes, helicopters, and drones, unmanned aerial and ground vehicles (UAV and UGV). For this reason, radar imaging, starting from data collected by such platforms, is gaining rapidly-increasing interest in the remote sensing community. However, a full exploitation of these smart and flexible radar systems requires the development and use of image formation techniques and reconstruction approaches able to properly deal with non-conventional data acquisition configurations. The other main issue is related to the necessity to operate in challenging operative conditions, by detecting, locating, and tracking targets. This entails the necessity to mitigate/overcome the effect of clutter, multipath, thanks to the adoption of signal processing strategies and electromagnetic modeling specifically devoted to “accurately describe” these complex electromagnetic scenarios, such as through wall imaging, urban canyon surveillance, and subsurface prospection, just to quote a few examples.

This Special Issue aims at providing an overview of recent scientific and technological advances in the field of radar imaging from smart and flexible platforms, 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:

Synthetic Aperture Radar (SAR) from aerial platforms (airplanes, helicopters, UAVs, drones);
Ground penetrating Radar (GPR) from aerial platforms (airplanes, helicopters, UAVs, drones);
Radar systems on terrestrial vehicles and UGV;
Ground based SAR for soil and infrastructure movements;
Compressive Sensing for Radar Imaging;
Passive Radar Imaging;
Through-wall and subsurface imaging;
Radar for urban surveillance;
Radar for situational awareness in inaccessible environments.

Prof. Moeness Amin
Dr. Stefano Perna
Dr. Francesco Soldovieri
Guest Editors

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Published Papers (11 papers)

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Editorial

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3 pages, 176 KiB

Open AccessEditorial

Editorial for Special Issue “Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms”

by Stefano Perna, Francesco Soldovieri and Moeness Amin

Remote Sens. 2020, 12(8), 1272; https://doi.org/10.3390/rs12081272 - 17 Apr 2020

Cited by 7 | Viewed by 2173

Abstract

Microwave radar imaging plays a key role in several civilian and defense applications, such as security, surveillance, diagnostics and monitoring in civil engineering and cultural heritage, environment observation, with particular emphasis on disasters and crisis management, where it is required to remotely sense the area of interest in a timely, safe and effective way. To address these constraints, a technological opportunity is offered by radar systems mounted onboard smart and flexible platforms, such as ground-based ones, airplanes, helicopters, drones, unmanned aerial and ground vehicles (UAV and UGV). For this reason, radar imaging based on data collected by such platforms is gaining interest in the remote sensing community. However, a full exploitation of smart and flexible radar systems requires the development and use of image formation techniques and reconstruction approaches able to exploit and properly deal with non-conventional data acquisition configurations. The other main issue is related to the need to operate in challenging environments, and still deliver high target detection, localization and tracking. These environments include through the wall imaging, rugged terrain and rough surface/subsurface. In these cases, one seeks mitigation of the adverse effects of clutter and multipath via the implementation of effective signal processing strategies and electromagnetic modeling. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

Research

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17 pages, 27154 KiB

Open AccessArticle

Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

by Davide Comite, Fauzia Ahmad, Traian Dogaru and Moeness Amin

Remote Sens. 2020, 12(5), 857; https://doi.org/10.3390/rs12050857 - 6 Mar 2020

Cited by 12 | Viewed by 3426

Abstract

We present an enhanced imaging procedure for suppression of the rough surface clutter arising in forward-looking ground-penetrating radar (FL-GPR) applications. The procedure is based on a matched filtering formulation of microwave tomographic imaging, and employs coherence factor (CF) for clutter suppression. After tomographic reconstruction, the CF is first applied to generate a “coherence map” of the region in front of the FL-GPR system illuminated by the transmitting antennas. A pixel-by-pixel multiplication of the tomographic image with the coherence map is then performed to generate the clutter-suppressed image. The effectiveness of the CF approach is demonstrated both qualitatively and quantitatively using electromagnetic modeled data of metallic and plastic shallow-buried targets. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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22 pages, 8109 KiB

Open AccessFeature PaperArticle

Small Multicopter-UAV-Based Radar Imaging: Performance Assessment for a Single Flight Track

by Ilaria Catapano, Gianluca Gennarelli, Giovanni Ludeno, Carlo Noviello, Giuseppe Esposito, Alfredo Renga, Giancarmine Fasano and Francesco Soldovieri

Remote Sens. 2020, 12(5), 774; https://doi.org/10.3390/rs12050774 - 29 Feb 2020

Cited by 17 | Viewed by 4413

Abstract

This paper deals with a feasibility study assessing the reconstruction capabilities of a small Multicopter-Unmanned Aerial Vehicle (M-UAV) based radar system, whose flight positions are determined by using the Carrier-Phase Differential GPS (CDGPS) technique. The paper describes the overall radar imaging system in terms of both hardware devices and data processing strategy for the case of a single flight track. The data processing is cast as the solution of an inverse scattering problem and is able to provide focused images of on surface targets. In particular, the reconstruction is approached through the adjoint of the functional operator linking the unknown contrast function to the scattered field data, which is computed by taking into account the actual flight positions provided by the CDGPS technique. For this inverse problem, we provide an analysis of the reconstruction capabilities by showing the effect of the radar parameters, the flight altitude and the spatial offset between target and flight path on the resolution limits. A measurement campaign is carried out to demonstrate the imaging capabilities in controlled conditions. Experimental results referred to two surveys performed on the same scene but at two different UAV altitudes verify the consistency of these results with the theoretical resolution analysis. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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18 pages, 8753 KiB

Open AccessArticle

Crop Growth Monitoring with Drone-Borne DInSAR

by Gian Oré, Marlon S. Alcântara, Juliana A. Góes, Luciano P. Oliveira, Jhonnatan Yepes, Bárbara Teruel, Valquíria Castro, Leonardo S. Bins, Felicio Castro, Dieter Luebeck, Laila F. Moreira, Lucas H. Gabrielli and Hugo E. Hernandez-Figueroa

Remote Sens. 2020, 12(4), 615; https://doi.org/10.3390/rs12040615 - 12 Feb 2020

Cited by 38 | Viewed by 6991

Abstract

Accurate, high-resolution maps of for crop growth monitoring are strongly needed by precision agriculture. The information source for such maps has been supplied by satellite-borne radars and optical sensors, and airborne and drone-borne optical sensors. This article presents a novel methodology for obtaining growth deficit maps with an accuracy down to 5 cm and a spatial resolution of 1 m, using differential synthetic aperture radar interferometry (DInSAR). Results are presented with measurements of a drone-borne DInSAR operating in three bands—P, L and C. The decorrelation time of L-band for coffee, sugar cane and corn, and the feasibility for growth deficit maps generation are discussed. A model is presented for evaluating the growth deficit of a corn crop in L-band, starting with 50 cm height. This work shows that the drone-borne DInSAR has potential as a complementary tool for precision agriculture. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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17 pages, 6169 KiB

Open AccessArticle

On the Capabilities of the Italian Airborne FMCW AXIS InSAR System

by Carmen Esposito, Antonio Natale, Gianfranco Palmese, Paolo Berardino, Riccardo Lanari and Stefano Perna

Remote Sens. 2020, 12(3), 539; https://doi.org/10.3390/rs12030539 - 6 Feb 2020

Cited by 15 | Viewed by 4090

Abstract

Airborne Synthetic Aperture Radar (SAR) systems are gaining increasing interest within the remote sensing community due to their operational flexibility and observation capabilities. Among these systems, those exploiting the Frequency-Modulated Continuous-Wave (FMCW) technology are compact, lightweight, and comparatively low cost. For these reasons, they are becoming very attractive, since they can be easily mounted onboard ever-smaller and highly flexible aerial platforms, like helicopters or unmanned aerial vehicles (UAVs). In this work, we present the imaging and topographic capabilities of a novel Italian airborne SAR system developed in the frame of cooperation between a public research institute (IREA-CNR) and a private company (Elettra Microwave S.r.l.). The system, which is named AXIS (standing for Airborne X-band Interferometric SAR), is based on FMCW technology and is equipped with a single-pass interferometric layout. In the work we first provide a description of the AXIS system. Then, we describe the acquisition campaign carried out in April 2018, just after the system completion. Finally, we perform an analysis of the radar data acquired during the campaign, by presenting a quantitative assessment of the quality of the SLC (Single Look Complex) SAR images and the interferometric products achievable through the system. The overall analysis aims at providing first reference values for future research and operational activities that will be conducted with this sensor. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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20 pages, 8859 KiB

Open AccessFeature PaperArticle

Design and Analysis of a UWB MIMO Radar System with Miniaturized Vivaldi Antenna for Through-Wall Imaging

by Zhipeng Hu, Zhaofa Zeng, Kun Wang, Weike Feng, Jianmin Zhang, Qi Lu and Xiaoqian Kang

Remote Sens. 2019, 11(16), 1867; https://doi.org/10.3390/rs11161867 - 9 Aug 2019

Cited by 46 | Viewed by 8689

Abstract

The ultra-wideband (UWB) multi-input multi-output (MIMO) radar technique is playing a more and more important role in the application of through-wall detection because of its high resolution, lower antenna requirements, and efficient data capturing ability. This paper develops a novel UWB MIMO radar system using a stepped-frequency continuous-wave (SFCW) signal, which is designed to detect human targets behind the regular brick and concrete wall. In order to balance high range resolution and wall-penetration depth, a novel miniaturized Vivaldi antenna with desired bandwidth of 0.5–2.5 GHz was designed, simulated, manufactured, and successfully used in through-wall imaging. To suppress the artifacts in the focused image and reduce the computing complexity, the cross-correlation-based time domain back projection (CC-TDBP) algorithm was developed. In addition, a through-wall imaging model was established, based on which the effects of the wall on the refraction of electromagnetic (EM) waves and the reduction of velocity are compensated. Finally, different experiments were conducted for multiple stationary targets utilizing the designed radar system, and the improved BP-based algorithms are applied to focus the targets behind the wall more accurately. The reconstructed two-dimensional (2D) images illustrate that the designed MIMO radar system can successfully detect and image human targets in the air and behind the wall. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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22 pages, 50639 KiB

Open AccessArticle

The ASI Integrated Sounder-SAR System Operating in the UHF-VHF Bands: First Results of the 2018 Helicopter-Borne Morocco Desert Campaign

by Stefano Perna, Giovanni Alberti, Paolo Berardino, Lorenzo Bruzzone, Dario Califano, Ilaria Catapano, Luca Ciofaniello, Elena Donini, Carmen Esposito, Claudia Facchinetti, Roberto Formaro, Gianluca Gennarelli, Christopher Gerekos, Riccardo Lanari, Francesco Longo, Giovanni Ludeno, Mauro Mariotti d’Alessandro, Antonio Natale, Carlo Noviello, Gianfranco Palmese, Claudio Papa, Giulia Pica, Fabio Rocca, Giuseppe Salzillo, Francesco Soldovieri, Stefano Tebaldini and Sanchari Thakur Show full author list Hide full author list

Remote Sens. 2019, 11(16), 1845; https://doi.org/10.3390/rs11161845 - 8 Aug 2019

Cited by 18 | Viewed by 5332

Abstract

This work is aimed at showing the present capabilities and future potentialities of an imaging radar system that can be mounted onboard flexible aerial platforms, such as helicopters or small airplanes, and may operate in the UHF and VHF frequency bands as Sounder and as Synthetic Aperture Radar (SAR). More specifically, the Sounder operates at 165 MHz, whereas the SAR may operate either at 450 MHz or at 860 MHz. In the work, we present the first results relevant to a set of Sounder and SAR data collected by the radar during a helicopter-borne campaign conducted in 2018 over a desert area in Erfoud, Morocco, just after the conclusion of a system upgrading procedure. In particular, a first analysis of the focusing capabilities of the Sounder mode and of the polarimetric and interferometric capabilities of the SAR mode is conducted. The overall system, originally developed by CO.RI.S.T.A. according to a ASI funding set up in 2010, has been upgraded in the frame of a contract signed in 2015 between ASI and different private and public Italian Research Institutes and Universities, namely CO.RI.S.T.A., IREA-CNR, Politecnico di Milano and University of Trento. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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19 pages, 7641 KiB

Open AccessArticle

A Compressive Sensing-Based Approach to Reconstructing Regolith Structure from Lunar Penetrating Radar Data at the Chang’E-3 Landing Site

by Kun Wang, Zhaofa Zeng, Ling Zhang, Shugao Xia and Jing Li

Remote Sens. 2018, 10(12), 1925; https://doi.org/10.3390/rs10121925 - 30 Nov 2018

Cited by 9 | Viewed by 3496

Abstract

Lunar Penetrating Radar (LPR) is one of the important scientific systems onboard the Yutu lunar rover for the purpose of detecting the lunar regolith and the subsurface geologic structures of the lunar regolith, providing the opportunity to map the subsurface structure and vertical distribution of the lunar regolith with a high resolution. In this paper, in order to improve the capability of identifying response signals caused by discrete reflectors (such as meteorites, basalt debris, etc.) beneath the lunar surface, we propose a compressive sensing (CS)-based approach to estimate the amplitudes and time delays of the radar signals from LPR data. In this approach, the total-variation (TV) norm was used to estimate the signal parameters by a set of Fourier series coefficients. For this, we chose a nonconsecutive and random set of Fourier series coefficients to increase the resolution of the underlying target signal. After a numerical analysis of the performance of the CS algorithm, a complicated numerical example using a 2D lunar regolith model with clipped Gaussian random permittivity was established to verify the validity of the CS algorithm for LPR data. Finally, the compressive sensing-based approach was applied to process 500-MHz LPR data and reconstruct the target signal’s amplitudes and time delays. In the resulting image, it is clear that the CS-based approach can improve the identification of the target’s response signal in a complex lunar environment. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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18 pages, 4576 KiB

Open AccessArticle

Focusing High-Resolution Airborne SAR with Topography Variations Using an Extended BPA Based on a Time/Frequency Rotation Principle

by Chunhui Lin, Shiyang Tang, Linrang Zhang and Ping Guo

Remote Sens. 2018, 10(8), 1275; https://doi.org/10.3390/rs10081275 - 13 Aug 2018

Cited by 17 | Viewed by 4024

Abstract

With the increasing requirement for resolution, the negligence of topography variations causes serious phase errors, which leads to the degradation of the focusing quality of the synthetic aperture (SAR) imagery, and geometric distortion. Hence, a precise and fast algorithm is necessary for high-resolution airborne SAR. In this paper, an extended back-projection (EBP) algorithm is proposed to compensate the phase errors caused by topography variations. Three-dimensional (3D) variation will be processed in the time-domain for high-resolution airborne SAR. Firstly, the quadratic phase error (QPE) brought by topography variations is analyzed in detail for high-resolution airborne SAR. Then, the key operation, a time-frequency rotation operation, is applied to decrease the samplings in the azimuth time-domain. Just like the time-frequency rotation of the conventional two-step approach, this key operation can compress data in an azimuth time-domain and it reduces the computational burden of the conventional back-projection algorithm, which is applied lastly in the time-domain processing. The results of the simulations validate that the proposed algorithm, including frequency-domain processing and time-domain processing can obtain good focusing performance. At the same time, it has strong practicability with a small amount of computation, compared with the conventional algorithm. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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20 pages, 9780 KiB

Open AccessArticle

Focusing High-Resolution Highly-Squinted Airborne SAR Data with Maneuvers

by Shiyang Tang, Linrang Zhang and Hing Cheung So

Remote Sens. 2018, 10(6), 862; https://doi.org/10.3390/rs10060862 - 1 Jun 2018

Cited by 19 | Viewed by 4579

Abstract

Maneuvers provide flexibility for high-resolution highly-squinted (HRHS) airborne synthetic aperture radar (SAR) imaging and also mean complex signal properties in the echoes. In this paper, considering the curved path described by the fifth-order motion parameter model, effects of the third- and higher-order motion parameters on imaging are analyzed. The results indicate that the spatial variations distributed in range, azimuth, and height directions, have great impacts on imaging qualities, and they should be eliminated when designing the focusing approach. In order to deal with this problem, the spatial variations are decomposed into three main parts: range, azimuth, and cross-coupling terms. The cross-coupling variations are corrected by polynomial phase filter, whereas the range and azimuth terms are removed via Stolt mapping. Different from the traditional focusing methods, the cross-coupling variations can be removed greatly by the proposed approach. Implementation considerations are also included. Simulation results prove the effectiveness of the proposed approach. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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Other

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10 pages, 2066 KiB

Open AccessLetter

Drone-borne Differential SAR Interferometry

by Dieter Luebeck, Christian Wimmer, Laila F. Moreira, Marlon Alcântara, Gian Oré, Juliana A. Góes, Luciano P. Oliveira, Bárbara Teruel, Leonardo S. Bins, Lucas H. Gabrielli and Hugo E. Hernandez-Figueroa

Remote Sens. 2020, 12(5), 778; https://doi.org/10.3390/rs12050778 - 29 Feb 2020

Cited by 34 | Viewed by 7747

Abstract

Differential synthetic aperture radar interferometry (DInSAR) has been widely applied since the pioneering space-borne experiment in 1989, and subsequently with the launch of the ERS-1 program in 1992. The DInSAR technique is well assessed in the case of space-borne SAR data, whereas in the case of data acquired from aerial platforms, such as airplanes, helicopters, and drones, the effective application of this technique is still a challenging task, mainly due to the limited accuracy of the information provided by the navigation systems mounted onboard the platforms. The first airborne DInSAR results for measuring ground displacement appeared in 2003 using L- and X-bands. DInSAR displacement results with long correlation time in P-band were published in 2011. This letter presents a SAR system and, to the best of our knowledge, the first accuracy assessment of the DInSAR technique using a drone-borne SAR in L-band. A deformation map is shown, and the accuracy and resolution of the methodology are presented and discussed. In particular, we have obtained an accuracy better than 1 cm for the measurement of the observed ground displacement. It is in the same order as that achieved with space-borne systems in C- and X-bands and the airborne systems in X-band. However, compared to these systems, we use here a much longer wavelength. Moreover, compared to the satellite experiments available in the literature and aimed at assessing the accuracy of the DInSAR technique, we use only two flight tracks with low time decorrelation effects and not a big data stack, which helps in reducing the atmospheric effects. Full article

(This article belongs to the Special Issue Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms)

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