Non-destructive inspection of penetrable vertical structures demands innovative investigation paradigms and ad-hoc tools to support timely and efficient maintenance interventions. Although Ground Penetrating Radar (GPR) is an established technology, the inspection of large vertical structures with classical ground-based systems remains challenging when there is limited accessibility, the equipment is difficult to maneuver, the operator’s safety is placed at risk, and the time to perform the survey becomes long. A promising solution to address these limitations suggests the use of mini drones equipped with GPR systems. However, this possibility introduces new challenges in both system design and data processing. A practical approach for drone-based GPR monitoring involves adapting a traditional contact GPR system, combined with appropriate data processing techniques, to perform contactless surveys. This study delves deeper into this approach by comparing the imaging performance achieved when the same ground-coupled GPR system paired with a microwave tomography-based data processing is exploited for contact and contactless surveys. Experimental results related to the inspection of a reinforced concrete wall are presented and discussed.

Radar imaging algorithms generally exploit linear models of the electromagnetic scattering phenomenon. This assumption leads to qualitative and computationally effective data inversion schemes, which only account for direct scattering from targets, whereas multipath signal contributions are neglected. As a result, multipath ghosts, i.e. false targets reconstructed at positions where no real target exists, affect the radar images thus preventing a reliable interpretation of the observed scene. This paper proposes a fully data-driven deep learning approach based on a convolutional neural network and microwave tomography to face this challenge. The approach achieves multipath ghost suppression for the case of small targets in terms of probing wavelength. In the proposed training scheme, the tomographic image affected by ghosts represents the input of the network while a ghost-free reconstruction is the output. Numerical simulations addressing the detection of metallic rebars via ground penetrating radar are presented. As shown, the proposed ghost removal strategy is effective and robust to variations of the scenario parameters on which the network is trained. Finally, an experimental validation shows the effectiveness of the proposed strategy even in operative conditions.

This paper presents an imaging approach for Multiple Input Multiple Output Ground Penetrating Radar (MIMO GPR) systems working in down-looking contactless mode. The approach exploits a linear approximation of the scattering phenomenon and is based on a ray-based propagation model, which takes into account the presence of the air-soil interface. Accordingly, the Interface Reflection Point concept is extended to the case of MIMO GPR. The proposed approach performs the imaging in the 2D scalar case and applies the Truncated Singular Value Decomposition regularization scheme to perform the inversion. The effectiveness of the approach is assessed by processing synthetic and real data. The real data are referred to the lunar soil and have been collected by means of the Lunar Regolith Penetrating Radar, installed on the Chang’E-5 lander.

This paper proposes a three-dimensional imaging approach for contactless ground penetrating radar surveys. The imaging problem is formulated in the linear inverse scattering context and solved by using the Singular Values Decomposition tool. A ray-based model accounting for the electromagnetic signal propagation into an inhomogeneous medium is developed to accurately evaluate the kernel of the integral equation to be inverted. Under the proposed model, an analysis of the spatial resolution performance is carried out as a function of the geometrical and electromagnetic parameters of the scenario. To this end, theoretical concepts based on diffraction tomography and the Singular Value Decomposition of the scattering operator are exploited. Reconstruction results based on full-wave simulated data assess the feasibility of the imaging approach.

This article investigates the capabilities of 24 GHz frequency-modulated continuous-wave (FMCW) multiple-input–multiple-output (MIMO) radar technology to retrieve sea surface currents and directional wave spectra. A procedure based on the dispersion relation, which was previously applied to process X-band marine radar data, is here exploited. The estimation performance of the radar sensor is first assessed by numerical tests in the case of synthetic sea wave fields with known characteristics in terms of wave direction and surface currents. Finally, the estimation procedure is assessed on real data collected at San Vincenzo quay in the port area of Naples, Italy. The achieved results are encouraging and highlight that 24 GHz FMCW MIMO radar is a viable technology for sea wave monitoring.

Ground-penetrating radar inspection of vertical structures, such as columns or pillars, is relevant in several applicative contexts. Unlike conventional subsurface prospecting, where the medium is accessible only from one side, the columns can be probed from various sides with measurement domains possibly encircling the structure. This makes it possible to retrieve more information about the scene, thanks to an increased view and data collection diversity. This article proposes an imaging approach for structures probed all around via vertical scans. The approach faces the imaging as a full 3-D electromagnetic inverse scattering problem and accounts for the vectorial nature of the scattering phenomenon. Moreover, the imaging approach is based on an approximate model of scattering and the inversion is regularized by means of the truncated singular value decomposition to produce stable and accurate results. The reconstruction capabilities of the proposed imaging approach are evaluated in terms of the achievable spatial resolution. To this end, a numerical analysis exploiting synthetic data allows investigating how the imaging quality depends on the number of vertical scans. Reconstruction results referred to data gathered in controlled conditions provide an experimental assessment of the achievable imaging capabilities.

Ground-penetrating radars operating at a stand-off distance from the probed domain are attractive diagnostic tools in several contexts. Despite notable advantages offered in terms of noninvasiveness and flexibility, the usage of stand-off configurations makes the imaging process more difficult. Indeed, an accurate reconstruction of the subsurface/hidden scene requires accounting for the presence of the air-soil interface into the scattering model. This article deals with a comparison of three different linear models for describing the scattering phenomenon under a stand-off configuration, where the presence of the layered medium is explicitly accounted for in the scattering model. The first model is rigorous and based on the spectral domain representation of the incident field and Green's function for the half-space scenario. The second model exploits a ray representation of the wave propagation from the radar to the target and vice versa by accounting for the refraction phenomenon at the interface. The third model is an approximated one, where the layered nature of the scenario is taken into account by means of an equivalent wavenumber, which allows a straightforward evaluation of the incident field and Green's function. The resolution performance of each inversion approach is assessed by means of a numerical analysis. Moreover, data referred to an experiment carried out in controlled conditions are processed and reconstructions are provided to support the comparative analysis among the three imaging approaches.

The Italian Space Agency (ASI) has recently entrusted CO.RI.S.T.A. with the development of a radar system that can be mounted onboard small airplanes or helicopters and may operate, at different frequencies belonging to the P-Band, either as Synthetic Aperture Radar (SAR) or as Sounder. In this work, we present preliminary results of the helicopter-borne desert campaign carried out with this system in 2018 over the Erfoud area, Morocco, in the frame of a project that has involved different public Italian Research Institutes and Universities.

This document is an errata corrige of the above paper[1].

The aim of this work is to show how an X-band radar system was able to instantly observe a phenomenon known as coastal upwelling. In fact, an X-band radar system is able to provide information about direction and intensity of the sea surface currents and waves in an area up to 3 nautical miles from the radar site. This capability, together with their flexibility and low cost, makes these devices useful tools for coastal monitoring and for the study of local small-scale phenomena as, for example, the upwelling. This phenomenon is, as generally recognized, the upward motion of deeper water while the surface ones are transported offshore by the stress of the wind blowing on the sea. Upwelled water is colder than surface water, moreover it is richer in nutrients and, as a consequence, it generates an increase in phytoplankton production (which in turn is able to boost food availability for fish populations) in the area affected by the upwelling. The characteristics of this phenomenon makes the X-band radar devices useful tools to support inshore fisheries, by monitoring environmental conditions at sea.

X-band marine radar systems represent a flexible and low-cost tool for the tracking of multiple targets in a given region of interest. Although suffering several sources of interference, e.g., the sea clutter, these systems can provide high-resolution measurements, both in space and time. Such features offer the opportunity to get accurate information not only about the target position/motion but also about the targets size. Accordingly, in this paper, we exploit emergent extended target tracking (ETT) methodologies in which the target state, typically position/velocity/acceleration, is augmented with the target length and width. In this paper, we propose an ETT procedure based on the popular probability hypothesis density filter, and in particular, we describe the extended target state through the gamma Gaussian inverse Wishart model. The comparative simplicity of the used models allows us to meet the real-time processing constraint required for the practical surveillance purposes. Real-world data from an experimental and operational campaign, collected during the recovery operations of the Costa Concordia wreckage in October 2013, are used to assess the performance of the proposed target tracking methodology. The full signal processing chain is implemented, and considerations of the experimental results are provided. Important nonideal effects, common to every marine radar, are observed and discussed in relation to the assumptions made for the tracking procedure.

This letter deals with the analysis of a novel data processing approach to estimate the local depth in a shallow coastal area starting from data collected by an in situ X-band radar system. The reconstruction approach is based on the maximization of the normalized scalar product (NSP) between the measured and the theoretical wave dispersion relation, which embeds the dependence on the searched for parameter (local depth). The use of NSP approach allows obtaining a high-resolution spatial map of the investigated area, and a thorough statistical analysis is carried out by comparing the local depth estimation results with the ground-truth data made available by a multi-beam echo-sounder survey. In addition, the improved accuracy of the NSP approach is demonstrated with respect to other methods previously used for the analysis of the same area.

This letter deals with the investigation of the performance of the REMOCEAN wave-radar system for sea state monitoring, with a specific focus to the navigation purposes. In particular, we present the results of the processing of data collected by an X-band wave-radar installed on the Cruise Roma, during the voyage from Civitavecchia (Italy) to Barcelona (Spain) and return, on 9th and 10th March, 2012. The effectiveness of the REMOCEAN data processing is analyzed by comparing the estimated sea state parameters with the expectation provided by the operational forecasting runs of the WaveWatchIII spectral modeling.

This work deals with the analysis of a novel data processing approach to estimate the local depth in a shallow coastal area starting from X-band radar data. The approach is based on the maximization of the Normalized Scalar Product (NSP) between the measured and the theoretical wave dispersion relations, which embed the dependence on the searched for parameters (current vector and depth). In the present work, we presented an improvement version of NSP approach able to estimate the local depth, which allows to obtain a high resolution spatial map (subpixel) of the investigated area. The performances of the NSP approach is evaluated by comparing the estimated bathymetry with the ground truth provided the multi-beam echo sounder reported on the same grid resolution of the bathymetric maps of the X-band radar images.

REMOCEAN is a remote sensing system for the wave and current monitoring, based on a nautical X-Band radar, usually deployed for navigation and ship traffic control. Here, we present the results obtained by the analysis of the data collected by the Remocean system, installed in the port of Giglio Island, during the storm of the 27 November 2012. For this test case, the effectiveness of the Remocean wave height reconstruction has been evaluated by analyzing the spectral slope and the statistical properties of the ocean waves and comparing them with independent measures provided by a buoy installed in the proximity the `Costa Concordia' shipwreck.

This work presents the experimental validation of a novel data processing approach to estimate the local depth in a shallow coastal area starting from X-band radar data. The approach is based on the maximization of the Normalized Scalar Product (NSP) between the measured and the theoretical wave dispersion relations, which embed the dependence on the searched for parameters (current vector and depth). The use of NSP approach allows obtaining a high resolution spatial map of the investigated area and a thorough statistical analysis of this approach is carried out by comparison with the ground truth data collected by a multibeam echo-sounder. Finally, the accuracy of the NSP approach is compared with the one achieved by other methods and prove to provide better results.

This letter deals with the use of the wave-radar REMOCEAN system for sea-state monitoring starting from images collected in the X-band at two different test sites. In particular, the measurement surveys were carried out at two coastal sites in the Gulf of Naples by means of the installation of the radar on a fixed and on a movable platform, respectively. The effectiveness of the system was also tested by means of a comparison between the REMOCEAN results and the high-frequency coastal radar observations, with emphasis to the sea surface current estimation.