**Contents**


### **Chunhui Lin, Shiyang Tang, Linrang Zhang and Ping Guo**


### **About the Special Issue Editors**

**Stefano Perna** completed his Laurea Degree (summa cum laude) in Telecommunication Engineering and his PhD in Electronic and Telecommunication Engineering, both at the Universita degli Studi ` di Napoli "Federico II", Naples, Italy, in 2001 and 2006, respectively. Since 2006, he has been with the Department of Engineering (DI) at the Universita degli Studi di Napoli "Parthenope", Naples, ` where he is currently a researcher in electromagnetics and teaches the courses "Antennas" and "Electromagnetics". He is currently also an adjunct researcher at IREA-CNR, Naples. Since 2015, he has collaborated with the Argentinian National Council of Technical and Scientific Research (CONICET) on activities relevant to the focusing and processing of SAR data acquired by the airborne SARAT system. In 2016, he was a visiting professor at the Departamento de Teor´ıa de la Senal y Comunicaciones of the Universitat Polit ˜ ecnica de Catalunya (UPC), Barcelona, Spain. He is ` an IEEE senior member. His main research interests are in the field of microwave remote sensing and electromagnetics: airborne SAR data modelling and processing, airborne differential SAR interferometry, modelling of electromagnetic scattering from natural surfaces, synthesis of antenna arrays; antenna characterization and measurement in anechoic and reverberating chambers. He is the co-author of about 100 papers published in international scientific journals or proceedings of international conferences in the field of electromagnetics and remote sensing.

**Francesco Soldovieri** is a research director at Institute for Electromagnetic Sensing of the Environment of CNR. He was General Chair of the International Workshop on Advanced Ground Penetrating Radar 2007 and General Co-Chair of the Ground Penetrating Radar Conference 2010. He was a member of the Editorial Board of IEEE-GRSL and now of IEEE-TCI and IEEE-TGRS, *Remote Sensing* (MDPI). He is Editor in Chief of *HERITAGE*, a MDPI journal devoted to cultural and natural heritage. He was the scientific coordinator of the FP7 projects ISTIMES and AMISS and the technical manager of the H2020 Project HERACLES. He was the President of the Division on Geosciences Instrumentation and Data Systems of the European Geosciences Union. His research interests include radar imaging, data processing for GPR, indoor surveillance, through-wall imaging, passive radars, integration of geophysical data, and radars for planetary exploration. He is the co-author of about 240 papers in national and international journals, and more than 350 conference proceedings.

**Moeness Amin** completed his BSc degree at the Faculty of Engineering, Cairo University in 1976, and his MSc at the University of Petroleum and Minerals in 1980. He then completed a PhD at the University of Colorado, Boulder, in 1984; all degrees are in Electrical Engineering. Since 1985, he has been with the Faculty of the Department of Electrical and Computer Engineering, Villanova University, Villanova, PA, USA, where he became the Director of the Center for Advanced Communications, College of Engineering, in 2002. Dr. Amin is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE); Fellow of the International Society of Optical Engineering (SPIE); Fellow of the Institute of Engineering and Technology (IET); and a Fellow of the European Association for Signal Processing (EURASIP). He is the recipient of: the 2017 Fulbright Distinguished Chair in Advanced Science and Technology; the 2016 Alexander von Humboldt Research Award; the 2016 IET Achievement Medal; the 2014 IEEE Signal Processing Society Technical Achievement Award; the 2009 Technical Achievement Award from the European Association for Signal Processing; the

2015 IEEE Aerospace and Electronic Systems Society Warren D White Award for Excellence in Radar Engineering. He is also the recipient of the IEEE Third Millennium Medal. Dr. Amin has over 800 journal and conference publications in signal processing theory and applications, covering the areas of wireless communications, radar, sonar, satellite navigations, ultrasound, healthcare, and RFID. He has co-authored 23 book chapters and is the editor of three books titled, *Through the Wall Radar Imaging*, *Compressive Sensing for Urban Radar*, and *Radar for Indoor Monitoring*, all published by CRC Press, in 2011, 2014, 2017, respectively.

### *Editorial* **Editorial for Special Issue "Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms"**

### **Stefano Perna 1,2,\*, Francesco Soldovieri 2 and Moeness Amin 3**


Received: 15 April 2020; Accepted: 15 April 2020; Published: 17 April 2020

**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 e ffective way. To address these constraints, a technological opportunity is o ffered 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 e ffects of clutter and multipath via the implementation of e ffective signal processing strategies and electromagnetic modeling.

This Special Issue (SI) is aimed 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.

The contributions of the SI can be generally classified into two groups.

The papers belonging to the first group [1–6] provide the description of the capabilities of newborn imaging radar systems designed to operate in challenging scenarios [1] or using smart and flexible aerial platforms, such as small airplanes [2], drones [3–5] or helicopters [6]. Overall, these contributions provide an interesting survey of the potential of lightweight and compact imaging radar sensors. The described systems cover a very wide range of the microwave spectrum, including the VHF band, up to the X-band. The papers under this group [5] provide a good survey of the radar hardware as well as the corresponding processing chain applied to the acquired data.

The contributions belonging to the second group [7–10] are focused on the description of novel data processing techniques aimed at achieving accurate radar imaging under complex acquisition geometries, such as in the case of airborne Synthetic Aperture Radar (SAR) [6–8], or in challenging scenarios, as in the case of Forward-Looking Ground-Penetrating Radar (FL-GPR) [9] or Lunar Penetrating Radar (LPR) [10].

As for the papers belonging to the first group, in [1], a newborn Ultra Wideband (UWB) Multiple-Input Multiple-Output (MIMO) radar system exploiting the Stepped-Frequency Continuous-Wave (SFCW) technology to detect human targets beyond the obstacle, is presented. More specifically, the design, as well as manufacturing processes leading to the realization of the overall radar system, which also includes a novel miniaturized Vivaldi antenna with 0.5–2.5 GHz bandwidth, are described. The radar system is successfully used for through-wall imaging applications by exploiting a data-processing algorithm based on the Cross-Correlation Time Domain Back Projection (CC-TDBP) technique.

In [2–4], two newborn SAR systems mounted onboard aerial platforms are presented. In particular, in [2], the imaging and topographic capabilities of a novel Italian airborne X-band SAR system, named AXIS, are discussed. The system is based on the Frequency-Modulated Continuous-Wave (FMCW) technology and is equipped with a single-pass interferometric layout. In this work, the description of the developed radar system is given along with a quantitative assessment of the quality of the SLC (Single Look Complex) SAR images and the interferometric products achievable through the system.

In [3,4], a novel Brazilian drone-borne SAR system operating in three di fferent frequency bands, namely the C-, L- and P-band, is presented. The system is capable of exploiting a single-pass interferometric configuration at C-band, and full-polarimetric configurations at the L- and P-band. In [3], the description of the system and a quantitative assessment of the results achieved by applying the Di fferential SAR Interferometry (DInSAR) technique to the L-band data is presented. The work in [4] is focused on an interesting precision farming application scenario enabled by the exploitation of the drone-borne SAR system. More specifically, a novel methodology for obtaining growth deficit maps with an accuracy down to 5 cm and a spatial resolution of 1 m is presented. The proposed methodology is based on the DInSAR technique.

Another light and compact imaging radar system mounted onboard a small Multicopter-Unmanned Aerial Vehicle (M-UAV) is presented in [5]. In this case, the radar operates with 1.7 GHz bandwidth centered at 3.95 GHz, and the flight positions are obtained through the Carrier-Phase Di fferential GPS (CDGPS) technique. In particular, the work describes the overall radar imaging system in terms of both hardware devices and data processing strategy. The system is validated by collecting and processing a dataset through a single flight track to provide focused images of on surface targets.

In [6], a helicopter-borne integrated Sounder/SAR system operating in the UHF and VHF frequency bands is described. More specifically, the Sounder operates at 165 MHz, whereas the full-polarimetric SAR could operate either at 450 MHz or at 860 MHz. The system is developed under the auspices of a contract between the Italian Space Agency (ASI) and di fferent private and public Italian Research Institutes and Universities. In this work, the first results relevant to a set of Sounder and SAR data, acquired during a campaign conducted in 2018 over a desert area in Erfoud, Morocco, are presented.

As for the papers belonging to the second group, they address the processing of three kinds of imaging radar data, namely, airborne SAR [7,8], FL-GPR [9] and LPR [10] data. For airborne SAR processing, exploitation of small and flexible aerial platforms to mount the radar systems makes the issues related to motion errors (that is, the attitude and position instabilities of the platform during the acquisition) coupled to the topographic variations of the observed scene even more critical; therefore, ad-hoc data processing strategies capable to properly account for these problems are needed.

In [7], the spatial variations induced on airborne SAR images by the motion errors are decomposed into three main parts: range, azimuth and cross-coupling terms. The cross-coupling variations are then corrected by means of a polynomial phase filter, whereas the range and azimuth terms are removed through Stolt mapping.

In [8], an extended back-projection approach is proposed to take into account the topography variations during the airborne SAR image formation process. In particular, the algorithm applies a time–frequency rotation operation to pursue high accuracy, while reducing the computational burden, typically required by standard back-projection algorithms operating entirely in the time-domain.

The FL-GPR allows fast scanning of large areas for real-time target detection, unlike its ground-coupled or near-ground down-looking GPR (DL-GPR) counterparts. This capability, however, comes at the expense of energy backscattered from the illuminated targets and limited image spatial resolution. Furthermore, the rough ground surface generates clutter that may obscure the buried targets, rendering target detection very challenging. In this respect, the work in [9] presents an enhanced imaging procedure for the suppression of the rough surface clutter arising in FL-GPR applications. The procedure is based on a matched filtering formulation of microwave tomographic imaging enhanced by a coherence factor (CF) scheme for clutter suppression.

The work in [10] is framed in the context of the planetary exploration and deals with the Lunar Penetrating Radar mounted onboard the Yutu lunar rover to detect the lunar regolith and the shallower subsurface geologic structures of the Moon. In particular, it is aimed at improving the capability of identifying response signals caused by discrete reflectors (such as meteorites, basalt and debris) beneath the lunar surface. To this end, a compressive sensing (CS)-based approach is proposed to estimate the amplitudes and time delays of the radar signals from LPR data.

In conclusion, this informative Special Issue would not have been possible without the hard work of all authors and reviewers. We also would like to extend our sincere appreciation to the Editorial O ffice of Remote Sensing for their professional and excellent managemen<sup>t</sup> work.

**Author Contributions:** The authors contribute equally to write this Editorial. All authors have read and agreed to the published version of the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.
