Search

Buried landmines and unexploded remnants of war are a constant threat for the population of many countries that have been hit by wars in the past years. The huge amount of casualties has been a strong motivation for the research community toward the development of safe and robust techniques designed for landmine clearance. Nonetheless, being able to detect and localize buried landmines with high precision in an automatic fashion is still considered a challenging task due to the many different boundary conditions that characterize this problem (e.g., several kinds of objects to detect, different soils and meteorological conditions, etc.). In this article, we propose a novel technique for buried object detection tailored to unexploded landmine discovery. The proposed solution exploits a specific kind of convolutional neural network (CNN) known as autoencoder to analyze volumetric data acquired with ground penetrating radar (GPR) using different polarizations. This method works in an anomaly detection framework, indeed we only train the autoencoder on GPR data acquired on landmine-free areas. The system then recognizes landmines as objects that are dissimilar to the soil used during the training step. Experiments conducted on real data show that the proposed technique requires little training and no ad hoc data preprocessing to achieve accuracy higher than 93% on challenging data sets.

The Seismic Microzonation of level 3 (SM3) is nowadays a world-wide accepted tool for the mitigation of seismic risk. The SM3 is a complex process involving different disciplines ranging from Geology and Applied Seismology to Structural and Geotechnical Engineering. The outcome of a SM3 is presented on a zoning map in terms of a selected ground shaking intensity parameter and susceptibility to main ground instability (soil liquefaction, settlements, landslides, fault ruptures). In an advanced SM3 study for a given area, four main interdisciplinary steps can be recognized: (1) definition of the reference input motions, (2) construction of the subsoil model, (3) performing of numerical analyses and computing of amplification factors, (4) identification of zones with different geotechnical hazard potential and drawing up of the SM3 map. After the 2016–2017 Central Italy seismic sequence, intensive studies have been performed to obtain SM3 maps in 137 municipalities most damaged by the earthquakes. The aim of these studies has been to obtain a clear background on site effects to perform a correct reconstruction of the municipalities. In the paper, main results and critical issues of the above-mentioned steps of SM3 procedure are discussed together with some remarks on the use of SM3 output in supporting seismic design for reconstruction.

Large landslides have affected the geomorphological evolution of most Alpine territories. Some catastrophic events also had a huge impact on the economic and cultural development of human societies. In the Bregaglia Valley and in nearby territories, evidences of settlements date back to the Roman age. In these areas, human activities always coexisted with the natural evolution of the valley, which has been characterized by recurrent natural events such as floods and landslides. Among these, the 1618 Piuro landslide was the one with the strongest impact, remaining impressed on the collective imagination and artistic representations. It erased an entire village and its 1000-2000 inhabitants few km East of Chiavenna, and it is still remembered as one of the worst tragedies in the history of the region. Understanding the evolutionary dynamics of such a geomorphologically active landscape, taking notes from the ancient or recent past, plays a central role in risk assessment and mitigation. In Piuro, such dynamics were investigated through a multidisciplinary approach, starting from the historical and archaeological analyses of the event and involving: (i) the geological/geomorphological characterization of the Last Glacial Maximum, to present palimpsest landscape of the valley through the realization of thematic maps, (ii) the stratigraphic interpretation of new boreholes crossing the landslide deposits and the deeper intra-mountain sedimentary valley fill, (iii) the realization of topographic, petrographic, geophysical (HVSR and MASW) and geo-mechanical surveys. In addition, the implementation of numerical models is on the way, to check different hypotheses on the predisposing factors, triggers, timing and evolution of the 1618 Piuro landslide. To increase the awareness of natural hazards in mountain settings and to promote a risk and resilience culture, all these acquired knowledge will be disseminated and shared with citizen, authorities and scientists in the frame of the Interreg project A.M.AL.PI.18. The fulfilment of a transboundary (Italian-Swiss) geo-cultural path will link other sites of historical and geological relevance through the territories of Bregaglia, Valchiavenna, Moesa and Ticino. Showing and telling the history of catastrophic landslides and their impacts on the involved communities, it will contribute to enhance the perception of beauty and the awareness of geo-hazard. The dissemination of knowledge and awareness is one main goal towards risk mitigation.The present work was co-funded through the EU, Regional Development European Fund, by Italian State, Helvetic Confederation and Cantons under the Interreg V-A IT-CH 2014-2020 Cooperation Program - A.M.AL.PI.2018 “Alpi in Movimento, Movimento nelle Alpi. Piuro 1618-2018", ID 594274 – Axis 2 “Cultural and natural enhancement”.

Among all the forensic applications in which it has become an important exploration tool, ground penetrating radar (GPR) methodology is being increasingly adopted for buried landmine localisation, a framework in which it is expected to improve the operations efficiency, given the high resolution imaging capability and the possibility of detecting both metallic and non-metallic landmines. In this context, this study presents landmine detection equipment based on multi-polarisation: a ground coupled GPR platform, which ensures suitable penetration/resolution performance without affecting the safety of surveys, thanks to the inclusion of a flexible ballistic shielding for supporting eventual blasts. The experimental results have shown that not only can the blanket absorb blast-induced flying fragments impacts, but that it also allows for the acquisition of data with the accuracy required to generate a correct 3D reconstruction of the subsurface. The produced GPR volume is then processed through an automated learning scheme based on a Convolutional Neural Network (CNN) capable of detecting buried objects with a high degree of accuracy.

Summary This paper presents the results from a Ground Penetrating Radar experimental campaign aiming at characterising the thickness of principal concrete elements of a subway tunnel, following relevant water infiltration phenomena that might have affected their integrity and possibly have degraded their structural stability. Given the requirements of penetration and image quality, the main purpose of the study was to identify an optimal equipment design capable of accurately determine thickness variations of the subsurface structures by the joint analysis of different operational frequency, particularly a 200 MHz and a 600 MHz equipment, and antenna polarisation. While suitable depth performance has been achieved for both frequency bands, the image quality is notably higher when the interference from the metallic elements is minimised, and hence the 600 MHz equipment oriented perpendicular to the armour level has proven to be the best option. Obtained results allow a centimetric characterisation of the vertical extension of the investigated structures, and confirm their deterioration.

Summary The advent of deep learning techniques had a huge impact in the geophysical community. Convolutional Neural Networks have been investigated for interpretation tasks and, lately, for seismic imaging problems traditionally approached with analytical methods. In this manuscript we employ a state-of-the-art CycleGAN for processing migrated images. We show an application scenario in which this post-processing machine transforms migrated images into corresponding reflectivity model of the subsurface. The proposed methodology achieves promising results in both synthetic and field data. The reconstructed reflectivity model exhibits a meaningful topology. However, the results suggest that computer-vision techniques need to be adapted to tackle the complexity of seismic imaging problems. For this purpose, we believe that geophysical knowledge can be embedded into more accurate network design.

Within the context of masonry texture identification and geometrical reconstruction, Ground Penetrating Radar (GPR) could emerge as an effective survey method, due to its high-resolution, scalable and non-destructive approach. This study has methodologically assessed operational advantages and weaknesses of the methodology when implemented for a seismic assessment purpose. In particular, the scope was to examine acquisition and post-processing strategies that could reliably highlight the presence or absence of specific construction features on which to develop a quantitative indication of the quality of the masonry. For this purpose, a high frequency 3D GPR acquisition on a plastered masonry wall incorporating different brick geometries, has been carried out. The acquisition was made along two different survey directions and analysing unfocussed and migrated radar slices. Thanks to a favourable antenna pattern alignment and achieved resolution enhancement, the focussed GPR data collected along the vertical mortar joints orientation have proven to be able to properly reconstruct the wall texture, providing therefore detailed and crucial information on its geometrical appearance.

Soil morphology plays a fundamental role in the vertical and lateral movements of solutes and water transport, providing knowledge regarding spatial distribution of its textural properties and subsurface dynamics. In this framework, the measured values of electrical conductivity are able to reveal the heterogeneity of soil that is present in a particular agricultural field and they are affected by more than one important physical characteristic: soil texture, organic matter, moisture content, and the depth of the clay pan. In the microwave region, these dynamics are known to exhibit a frequency dependent behaviour. This study explores the application of a Step Frequency Continuous Wave Ground Penetrating Radar (SFCW GPR) to shed light on the practical impact that these dependencies have on the imaging results, not only regarding the electrical characterisation of the subsurface morphology, but also in its correct interpretation. This information is of notable importance for determining water-use efficiency and planning precision-agriculture programs. The results clearly show visible and significant fluctuations of the amplitude levels, depending on the considered central frequency, demonstrating that the frequency dependence of electromagnetic properties of heterogeneous soil are significant and cannot be ignored if the aim is to properly define the subsurface attributes. The measurements also suggest that correlating the delineated variations might help in the identification of extended features and the classification of areas that possess similar properties in order to increase the confidence in monitoring soil resources.

The effectiveness of the ground penetrating radar (GPR) imaging process and its capability of correctly reconstructing buried objects is strictly bounded to a correct acquisition strategy, both in terms of data density and regularity. In some GPR applications, such as landmine detection, these requirements may not be fulfiled due to logistical limitations and environmental obstacles. In the light of autonomous platform, possibly driven by a positioning device, the knowledge of the maximum affordable grid irregularity is essential. This experimental work, employing a data set acquired at a landmine test site, provides a demonstration that the same information content could be maintained even with a sparser data grid, compared to the commonly adopted requirements, mitigating the pressing demand for a precise samples positioning.

Buried unexploded landmines are a serious threat in many countries all over the World. As many landmines are nowadays mostly plastic made, the use of ground penetrating radar (GPR) systems for their detection is gaining the trend. However, despite several techniques have been proposed, a safe automatic solution is far from being at hand. In this paper, we propose a landmine detection method based on convolutional autoencoder applied to B-scans acquired with a GPR. The proposed system leverages an anomaly detection pipeline: the autoencoder learns a description of B-scans clear of landmines, and detects landmine traces as anomalies. In doing so, the autoencoder never uses data containing landmine traces at training time. This allows to avoid making strong assumptions on the kind of landmines to detect, thus paving the way to detection of novel landmine models.

The determination of the degradation state of underground concrete tunnels is a crucial issue for maintaining and monitoring the performance of these infrastructures. In particular, if the tunnel is totally or partially submerged, concrete deterioration and consequent changes in both lining thickness and hydraulic conductivity can have dramatic effects on the amount of water inflow, leading to an increase in maintenance costs as well as to possible interruption of the infrastructure serviceability. The hydraulic conductivity of the concrete lining is here proposed as a proxy of the overall degradation state of the structure, being this property directly correlated to porosity and to the presence of interconnected fissures and cracks. The aim of this study is to propose a simple and completely non-destructive method to estimate the hydraulic conductivity of tunnel lining concrete. Provided the availability of easy-to-collect in situ geometrical and hydrogeological data (i.e. tunnel geometry, water inflow, water table level), the method relies on a back analysis to estimate the hydraulic conductivity of the concrete, performed via the finite element method to solve the seepage equations in porous media. Ground Penetration Radar technique is coupled to the modelling approach to gain accurate data about the current lining thickness. The proposed method has been applied to the study of a real case of underground tunnel, used to prove the model reliability. Moreover, once estimated the hydraulic conductivity and thickness of the concrete, the model can be used to generate curves linking the total water inflow in the tunnel as a function of the groundwater level variations, allowing a real-time monitoring of the current hydraulic state of the infrastructure. This methodology, which can be considered of general validity and easy to be extended for the study of any underground tunnel, provides a simple and effective tool useful to prioritize maintenance works and to evaluate the consequences of different hydraulic scenarios.

Relining is a trenchless technology of recoating the inside walls of damaged water pipes using composite materials. In the Safe Pipe project, co-financed by Regione Lombardia, alternative polymeric materials for relining the drinking water distribution system of the city of Milan have been developed. Relining polymers have been evaluated for their toxicity. The identification of product impurities was performed by HPLC/HRMS and GC/MS analysis and safety evaluation was conducted applying toxicity data, when available, or applying QSAR models. Results showed low level of toxic substances in polymerized resins and in water samples in a migration/leaching test performed in a field experiment.

Ground Penetrating Radar (GPR) is widely recognised as an operationally useful sensor for mine detection as it can offer better detection performance than the ubiquitous metal detector in the presence of low-metal content mines. However, GPR has to overcome many potential sources of false alarm due to clutter and battlefield debris, which lower the efficiency of the sensor. This paper analyses a set of experimental data collected in a recent multi-offset GPR measurement campaign with inert landmines composed of different assemblies buried in sandy soil. The aim of the work is to evaluate the key differences observed by a radar system when the transmitter and the receiver are moved apart, as a function of their distance and hence when the illuminated section of the target is diversified. The results of the comparison between the collected multi-offset profiles show that using a bistatic geometry could represent a strategy to reconstruct composite objects with finer and better details.

Water front in concrete exposed to rapid heating is the layer where water vaporization and the subsequent pore pressure rise take place. Pore pressure is one of the main triggering factors in heat-induced explosive spalling (relevant for structures, such as tunnels, exposed to fire), while moisture migration influences concrete radiation shielding capability (important in containment shells of nuclear power plants and radioactive waste repositories). Hence, the experimental monitoring of water front in concrete at high temperature is a very interesting – though challenging – task. In a recent experimental campaign carried out at Politecnico di Milano, promising results have been obtained by coupling pore pressure-temperature measurements and water front monitoring through Ground-Penetrating Radar. This technique was implemented in a fire test performed on a concrete slab heated at the bottom face and proved to be effective in detecting the position of the water front during heating. The combination with pressure measurement allowed to confirm that pressure peaks are achieved in correspondence of the water front.

The presence of buried landmines is a serious threat in many areas around the World. Despite various techniques have been proposed in the literature to detect and recognize buried objects, automatic and easy to use systems providing accurate performance are still under research. Given the incredible results achieved by deep learning in many detection tasks, in this paper we propose a pipeline for buried landmine detection based on convolutional neural networks (CNNs) applied to ground-penetrating radar (GPR) images. The proposed algorithm is capable of recognizing whether a B-scan profile obtained from GPR acquisitions contains traces of buried mines. Validation of the presented system is carried out on real GPR acquisitions, albeit system training can be performed simply relying on synthetically generated data. Results show that it is possible to reach 95% of detection accuracy without training in real acquisition of landmine profiles.

This paper focuses on the application of ground penetrating radar (GPR) technique for civil engineering purposes, addressing the issues related to wave polarisation and antennas geometry. Even if polarisation of GPR signal is often an underestimated feature during data analysis and post processing, detection or avoidance of a specific target can be managed handling its polarimetric response. This opportunity is of high importance in this field of application, where the mixture of target with different polarimetric response is a commonly encountered situation. To provide an insight of this, two multicomponent GPR surveys have been performed: a first survey to show the effect of antenna-target mutual alignment variation and a second experiment in which the benefits of acquiring with different antenna arrangements are clearly evident. Because each antenna arrangement is sensitive towards different features of the received wavefield, this strategy is able to discriminate targets depending on their geometrical...

Ground penetrating radar (GPR) is widely used in subsurface investigations for extracting the position and the route followed by the utility, an issue that gains more and more importance when considering the cost related to trench damage and disruptions. However, it has been noted that various targets of GPR surveys, especially linear and elongated targets, have polarization-dependent scattering characteristics. This implies that the visibility of a subsurface scatterer in the acquired data depends on the used antenna configuration and its orientation with respect to the feature to be imaged. Furthermore, wave attributes could be modified by the surrounding soil anisotropy and heterogeneity degree. As the GPR antennas are composed of directional dipoles, any changes in the propagation plane of the returning wave affects the recording of GPR data. This work presents an approach based on a combination of mutually orthogonal GPR 3D data volumes through which polarization issues can be overcome, ensuring target detection even when the position and material are adverse. The strategy is evaluated through two field examples: in homogeneous soil this technique fully recovers the polarization mismatch, providing results that are closely similar to the ones that would be obtained with the optimal configuration; in heterogeneous environments it overcomes the wavelet alteration, depolarization included, strongly enhancing the signal to noise ratio and improving target reconstruction.

The long-term research experience of the authors has highlighted the importance of gaining knowledge of the building through experimental investigation. Recently the authors intensively studied the Syracuse Cathedral (Sicily, Italy) to evaluate the structural state of the preservation of the pillars. The Cathedral of Syracuse was built in different phases on an ancient Greek temple from the fifth century bc and modified throughout later centuries. The pillars of the central nave, obtained by cutting the temple cell walls, show a complex situation of damage and repairs. An investigation program (including radar, sonic, and ultrasonic tests, for example) has been recently planned, aimed to design the preservation and restoration actions. An accurate geometric survey of the surface problems and defects allowed the localization of the most damaged area, suggesting the need for further control by non-destructive testing (NDT). The results obtained from this survey were compared with the results of the other ty...

This paper deals with the need for transparency and good governance in insurance companies in the wake of recent scandals in the financial services. It also shows that socially responsible investing can be a tricky activity because of how questionable products are often linked with socially acceptable ones. The Geneva Papers (2005) 30, 467–476. doi:10.1057/palgrave.gpp.2510044

This paper presents the results obtained from the combination of co-pole GPR data collected along perpendicular directions. The scope is to demonstrate how this approach can efficiently overcome pitfalls of traditional single orientation surveys and ensure target detection regardless of their geometrical and physical properties. This is of high importance especially when acquiring across targets that show directional dependencies of the preferential scattering components. This work relies on four field examples, each of them illustrating in detail the improvements and the advantages that a single image resulting from the stack of the two volumes can show, in particular what concerns target imaging.

The two-step approach is a fast algorithm for 3D migration originally introduced to process zero-offset seismic data. Its application to monostatic GPR (Ground Penetrating Radar) data is straightforward. A direct extension of the algorithm for the application to bistatic radar data is possible provided that the TX-RX azimuth is constant. As for the zero-offset case, the two-step operator is exactly equivalent to the one-step 3D operator for a constant velocity medium and is an approximation of the one-step 3D operator for a medium where the velocity varies vertically. Two methods are explored for handling a heterogeneous medium; both are suitable for the application of the two-step approach, and they are compared in terms of accuracy of the final 3D operator. The aperture of the two-step operator is discussed, and a solution is proposed to optimize its shape. The analysis is of interest for any NDT application where the medium is expected to be heterogeneous, or where the antenna is not in direct contact with the medium (e.g., NDT of artworks, humanitarian demining, radar with air-launched antennas).

Terrorism is posing new technological problems to security forces. The need of checking for hazardous targets such as explosives, bombs, weapons, etc., hidden inside unexpected packages or embedded within blocks of other materials is increasing. GPR has been already explored for AntiPersonnel Mines (APM) detection and most prototypes are based on single or arrays of antennas surveying the suspected area from a distance of a few centimeters. We are exploring a flexible solution that is expected to be: a) applicable to different scenarios such as soil inspections (as for landmines) but also investigations on packages, blocks of materials, walls, etc., b) adaptable to a set of antennas to ensure proper penetration and resolution, c) safe for operator and equipment, d) accurate in antenna positioning to produce 3D reconstructions, e) based on a survey procedure that allows the contact with the medium to eliminate the energy loss produced by the non-contact approach. A single antenna plus an armored PSG (Pad System for Georadar) seem to fulfill the requirements. Radar performances were tested to explore the effects of the armor material. Tests were executed on the landmine field managed by the Joint Research Center (JRC) in Ispra (Italy). The results demonstrate the feasibility and the advantages of this solution.

The investigation target is a landfill situated in Italy. The area covers a surface of about 7.000 m. At the beginning the area was used for production of inert material. Later the area was used to dispose the industrial waste of a company operating in the iron and steel field. In the eighties, the landfill became exhausted and the activity for the rehabilitation of the site started. Within these activities an electrical survey was performed. In this work, the GPR survey carried out in July 2003 is described. 250 MHz and 50 MHz antennas were used: the analysis of the profiles shows a strong difference in the penetration between the landfill and the surrounding fields. Due to the high conductivity of the industrial waste, the penetration in the landfill is very low while the penetration outside the landfill can reach a depth of several meters. As a result, GPR is a successful method and was extensively applied for accurate mapping the lateral extension of the landfill and for estimating possible variations of the contamination level. Instead, the DC method is the most appropriate technique for an approximate estimate of the landfill depth.

A prototype of an ultra-high frequency radar system (2- 60Hz) has been developed at the RST laboratory within the framework of the HOPE project funded by the European Community and aimed at integrating three sensors (metaldetector, GPR and microwave radiometer) into a unique portable system for humanitarian demining. An advanced prototype of the GPR sensor assembled with the dual metal coil MD sensor has been recently tested at the outdoor facilities of the Joint Research Center in Ispra (Italy). The test field specifically prepared by JRC consists of a unique target scenario that is recreated under different type of soils and surface conditions. The target scenario includes different type of mines and false alarm targets like stone, wood, metallic or plastic objects. The dataset collected during this test are quite interesting for planning the future improvements of both the hardware and the software solutions. The data has been processed with a 3D imaging software specifically developed by the authors for the HOPE project. The preliminary results are encouraging for some scenarios whereas some others seem to be really demanding for the GPR sensor.

GPR applications to historical buildings have been cautiously increasing in recent years. The investigation of the wooden structural elements in historical buildings is essential to plan the restoration works. We discuss three case histories where 2D and 3D GPR surveys were executed to solve problems posed by restorers. The first survey was carried out to locate the beams of a wooden floor in a two hundred years old house in Pescate (Italy). The second survey was carried out in a stone masonry house of the 19th century in Lecco (Italy) to investigate the beam-wall connection. The third survey was carried out in a five hundred years old church in Busto Arsizio (Italy) to detect all the wooden elements. In this case some beams were totally hidden inside the brick and stone walls.

Sonic and radar investigations are frequently used in conjunction with other NDT techniques to assess the safety conditions of historical buildings, to understand the construction techniques and to locate internal in-homogeneities or hidden wood or metal elements. Both sonic and radar equipment can be used to produce tomographic sections that show the velocity map within a construction element like a wall or a pier. Radar data can be also processed by back-projecting the received energy in order to produce attenuation maps that can be interpreted to understand the absorption and scattering properties of the construction materials. Unfortunately, this method is not applicable to sonic data because sonic amplitudes are influenced by too many factors besides absorption. A promising alternative method consists of back-projecting the frequency downshift effect produced by absorption. The reliability of this approach is discussed for the specific application to historical buildings by presenting real data examples. The discussion shows the additional information that can be extracted from these sonic attenuation maps. By extending the approach to radar data, new attenuation maps can be obtained and compared to those derived from amplitude back-projection. Since the two inversion methods are based on the analysis of different effects produced by attenuation, i.e., frequency downshift and amplitude decay respectively, the attenuation maps are not necessarily equivalent and the analysis of similarities and differences can be quite useful to constrain the final interpretation of all the tomographic images.

For an accurate imaging of ground penetrating radar data the polarization characteristics of the propagating electromagnetic (EM) wavefield and wave amplitude variations with antenna pattern orientation must be taken into account. For objects that show some directionality feature and cylindrical shape any misalignment between transmitter and target can strongly modify the polarization state of the backscattered wavefield, thus conditioning the detection capability of the system. Hints on the depolarization can be used to design the optimal GPR antenna survey to avoid omissions and pitfalls during data processing.This research addresses the issue of elongated target detection through a multi azimuth (or multi polarization) approach based on the combination of mutually orthogonal GPR data. Results from the analysis of the formal scattering problem demonstrate how this strategy can reach a scalar formulation of the scattering matrix and achieve a rotational invariant quantity. The effectiveness of the algorithm is then evaluated with a detailed field example showing results closely proximal to those obtained under the optimal alignment condition: detection is significantly improved and the risk of target missing is reduced.

The assessment of the building conditions with NDT techniques is necessary to estimate their safety and to plan their restoration. In the last few years, the GPR technology has been improved to meet the requirements needed for this application, e.g., many manufacturers have developed new high frequency shielded antennas to ensure very high resolution images. 3D GPR reconstructions are particularly interesting to investigate the complex geometry of structural elements. To execute a 3D GPR survey it is necessary to acquire a regular matrix of GPR traces. Accuracy in antenna position and orientation is very important for a successful application of a 3D migration software to produce images that can be directly interpreted by the end-users. An array of antennas helps to ensure a regular spacing in the cross-line direction of the survey but the array is heavy and large so that it might be inappropriate to investigate vertical elements like walls, pillars and columns and to adapt to the shape of the surface decorations especially in historical buildings. For these reasons, we developed the PSG (Pad System for Georadar), patented by Politecnico of Milano. It is a new easy-to-use and low cost positioning system to execute 3D GPR surveys with a monochannel equipment. The system can work both on horizontal and vertical elements. We produced some prototypes with different materials and we found the system really useful to solve many problems posed by the restorers of historical buildings such as the analysis of beam-wall connections, the reconstruction of the internal structure of vaults, the detection of wooden frames hidden inside masonry walls, etc.. The system is also quite useful to speed up the surveys finalized to produce effective 3D maps of the reinforcements in concrete structures.

In the first three meters of the urban subsoil there are many types of utilities but their actual location is often unknown. Different companies manage the various types of utilities and till now the regulations of many countries do not force them to draw and regularly update the maps of their installations. As a result, the maintenance of the utility net and the utilization of the no dig technology are more and more difficult. 3D GPR investigations are the most effective method to map the utilities but the GPR systems developed till now to perform this type of survey are based on multi-channel solutions with an array of antenna so that the equipment is expensive and difficult to use on small areas (e.g., sidewalk, narrow streets, ...) or where it is not possible to stop the human activities (e.g., traffic). To overcome these difficulties, we designed a low-cost and easy-to-use positioning system named PSG (Pad System for Georadar, patent of Politecnico of Milano) to collect a regular grid of GPR data with a single antenna and with the accuracy required to generate 3D migrated images. The prototype testing proves that the system is effective, flexible and quite convenient in many real situations.