Ground-penetrating radar (GPR) was firstly used in traffic infrastructure surveys during the first half of the Seventies for testing in tunnel applications. From that time onwards, such non-destructive testing (NDT) technique has found exactly in the field of road engineering one of the application areas of major interest for its capability in performing accurate continuous profiles of pavement layers and detecting major causes of structural failure at traffic speed. This work provides an overview on the main signal processing techniques employed in road engineering, and theoretical insights and instructions on the proper use of the processing in relation to the quality of the data acquired and the purposes of the surveys

Ground penetrating radar (GPR) is traditionally applied to smooth surfaces in which the assumption of halfspace is an adequate approximation that does not deviate much from reality. Nonetheless, using GPR for internal structure characterization of tree trunks requires measurements on an irregularly shaped closed curve. Typical hyperbola-fitting has no physical meaning in this new context since the reflection patterns are strongly associated to the shape of the tree trunk. Instead of a clinical hyperbola, the reflections give rise to complex-shaped patterns that are difficult to be analyzed even in the absence of clutter. In the current paper, a novel processing scheme is described that can interpret complex reflection patterns assuming a circular target subject to any arbitrary shaped surface. The proposed methodology can be applied using commercial handheld antennas in real-time avoiding computationally costly tomographic approaches that require the usage of custom-made bespoke antenna arrays. The validity of the current approach is illustrated both with numerical and real experiments.

Effective quality assurance and quality control inspections of new roads as well as assessment of remaining service-life of existing assets is taking priority nowadays. Within this context, use of ground penetrating radar (GPR) is well-established in the field, although standards for a correct management of datasets collected on roads are still missing. This paper reports a signal processing method for data acquired on flexible pavements using GPR. To demonstrate the viability of the method, a dataset collected on a real-life flexible pavement was used for processing purposes. An overview of the use of non-destructive testing (NDT) methods in the field, including GPR, is first given. A multi-stage method is then presented including: (i) raw signal correction; (ii) removal of lower frequency harmonics; (iii) removal of antenna ringing; (iv) signal gain; and (v) band-pass filtering. Use of special processing steps such as vertical resolution enhancement, migration and time-to-depth conversion are finally discussed. Key considerations about the effects of each step are given by way of comparison between processed and unprocessed radargrams. Results have proven the viability of the proposed method and provided recommendations on use of specific processing stages depending on survey requirements and quality of the raw dataset.

This paper reports on the GPR-based assessment of railway ballast which was progressively "polluted" with a fine-grained silty soil material. It is known how the proper operation of a ballast track bed may be undermined by the presence of fine-grained material which can fill progressively the voids between the ballast aggregates and affect the original strength mechanisms. This occurrence is typically defined as "fouling". To this effect, a square-based methacrylate tank was filled with ballast aggregates in the laboratory environment and then silty soil (pollutant) was added in different quantities. In order to simulate a real-life scenario within the context of railway structures, a total of four different ballast/pollutant mixes were introduced from 100% ballast (clean) to highly-fouled (24 %). Ground-penetrating radar (GPR) systems equipped with different air-coupled antennas and central frequencies of 1000 MHz and 2000 MHz were used for testing purposes. Several processing methods were applied in order to obtain the dielectric permittivity of the ballast system under investigation. The results were validated using the "volumetric mixing approach" (available within the literature) as well as by performing a numerical simulation on the physical models used in the laboratory. It is important to emphasize the significance of the random-sequential absorption (RSA) paradigm coupled with the finite-difference time-domain (FDTD) technique used during the data processing. This was proved to be crucial and effective for the simulation of the GPR signal as well as in generating synthetic GPR responses close to the experimental data.

Nowadays, severe meteorological events are always more frequent all over the world. This causes a strong impact on the environment such as numerous landslides, especially in rural areas. Rural roads are exposed to an increased risk for geotechnical instability. In the meantime, financial resources for maintenance are certainly decreased due to the international crisis and other different domestic factors. In this context, the best allocation of funds becomes a priority: efficiency and effectiveness of plans and actions are crucially requested. For this purpose, the correct localisation of geotechnically instable domains is strategic. In this paper, the use of Ground-Penetrating Radar (GPR) for geotechnical inspection of pavement and sub-pavement layers is proposed. A three-step protocol has been calibrated and validated to allocate efficiently and effectively the maintenance funds. In the first step, the instability is localised through an inspection at traffic speed using a 1-GHz GPR horn launched antenna. The productivity is generally about or over 300Km/day. Data are processed offline by automatic procedures. In the second step, a GPR inspection restricted to the critical road sections is carried out using two coupled antennas. One antenna is used for top pavement inspection (1.6GHz central frequency) and a second antenna (600MHz central frequency) is used for sub-pavement structure diagnosis. Finally, GPR data are post-processed in the time and frequency domains to identify accurately the geometry of the instability. The case study shows the potentiality of this protocol applied to the rural roads exposed to a landslide