In this work, the novel imaging algorithm of synthetic aperture radar (SAR) system to be used in near-range based on fractional Fourier transform is presented. The algorithm projects the target reflectivity function onto pseudopolar coordinates and focuses along the short time through the fractional Fourier transform. The discrete format procedure for imaging near-range target is also introduced in this paper. The numerical simulation results show that the algorithm is more suitable for the high-precision synthetic aperture radar imaging in the near field.
Satellite Remote-Sensing has been successfully applied for detection of natural-hazards, (e.g. seismic events, landslides and subsidence) and transport infrastructure monitoring over the last few years. Persistent Scatterer SAR Interferometry (PSI), is a satellite remote sensing technique able to measure ground displacements over the time. More specifically, the PSI technique is an evolution of the DInSAR technique and it is based on a statistical multi-temporal differential interferogram analysis. This allows to determine coherent stable-pixels over a data-stack of SAR images, in order to identify potential ground displacements. This study aims at demonstrating the potential of the PSI technique as an innovative health-monitoring methodology for the structural integrity of bridges. For this purpose, X‐Band COSMOSkyMed images provided by the Italian Space Agency (ASI) were acquired and processed in order to detect structural displacements of the Rochester Bridge in Rochester, UK. Outcomes of this investigation outlined the presence of various PSs over the inspected bridge, which were proven useful to achieve a more comprehensive monitoring methodology and to assess the structural integrity of the bridge. This research paves the way for the development of a novel interpretation approach relying on the integration between remote-sensing technologies and on-site surveys to improve upon current maintenance strategies for bridges and transport assets.
The monitoring and conservation of natural assets are nowadays increasingly important, as the emergence of unknown pathogens endangers tree survival. In this respect, root systems are affected by fungal infections that cause root rot and ultimately contribute to the death of trees. Such diseases can quickly spread to surrounding trees and affect wider areas. Since these decays do not usually show visible symptoms, early identification is key to the protection of trees. Within this framework, non-destructive testing (NDT) methods are becoming increasingly popular, as they are faster and more flexible than destructive methods. Specifically, ground penetrating radar (GPR) is emerging as an accurate geophysical tool for tree roots mapping. Recent research has focused on the implementation of automated algorithms for root mapping in a 3D environment and the investigation of root mass density. This research aims to investigate the changes occurring in the frequency spectrum of the GPR signal during root system surveys. To this extent, advanced signal processing techniques (both in time and frequency domain) are applied, to eliminate noise-related information and the disturbance induced by the presence of other features (i.e. pavement layers or underground utilities). The proposed processing framework can be applied for expeditious analyses or on trees difficult to access, where more comprehensive survey methods are not applicable. The results of the application of this methodology to a real-case scenario showed the potential of the applied procedure and will lead to the development of a new approach for investigating root systems using GPR.
The satellite PSI Interferometry is a radar-based remote-sensing technique, which is capable of monitoring and measuring displacements with a high precision of the Earth’s surfaces by means of multi-temporal acquisitions. These are collected without interfering in any way with the operating conditions of the transport infrastructure as opposed to the common non-destructive survey methodologies (e.g. GPS, accelerometer, total stations). Nowadays, the use of medium ground-resolution SAR-datasets, acquired by C-Band sensors (operating at a frequency of 5.4 GHz), allow to conduct computationally affordable analyses, detecting displacements with a centimeter accuracy of the measurement. Furthermore, the use of images acquired by the new generation of high-resolution X-Band radar sensors (operating at a frequency of 9.6 GHz), allow to increase the ground-resolution and achieve a millimeter displacement-resolution This study aims at demonstrating the potential of the PSI remote-sensing technique to develop and formulate an innovative health-monitoring methodology and approach for structural assets such as bridges, using a multi-frequency satellite resolution. For this purpose, in this study C‐Band Sentinel‐1A SAR products provided by the European Space Agency (ESA), and X‐Band COSMO‐Skymed products provided by the Italian Space Agency (ASI) were acquired and processed. Furthermore, a PSI analysis was developed to monitor and detect structural displacements of a bridge of historical values. Outcomes of this investigation outlined the presence of various PS over the inspected bridge, which were proven useful to achieve a more comprehensive health monitoring and the assessment of the structural integrity of the bridge. This research paves the way for the development of a novel interpretation approach relying on the integration between remote-sensing data and non-destructive information collected on-site (e.g., GPR surveys and Laser Scanner), to improve and optimize current maintenance process of transport assets.
Smart monitoring of critical civil engineering infrastructures has become a priority nowadays as ageing of construction materials may have dramatic consequences on the community. The issue is exacerbated as it applies to many structures at the network level rather than to single structures or limited areas. To this effect, catalogues for assessment of decay conditions and identification of maintenance actions are crucial pieces of information for infrastructure management purposes. Within this context, innovative non-destructive methods, such as space-borne techniques, have been increasingly used for monitoring purposes in the past two decades. Among these, the Interferometric Synthetic Aperture Radar (InSAR) imagery technique is gaining momentum nowadays. This method is used to monitor ground and infrastructure displacements at the large scale with a millimeter resolution. It can compare radar satellite images over time, and it is capable to measure variations accurately using interferometry. An advantage of using InSAR techniques is that these are not affected by cloudiness as well as lighting conditions, since data can be also collected at night time. On the contrary, InSAR is computational-demanding as it requires to filter out unnecessary information from the entire captured area to obtain data on the target domain. Most common applications include landslide assessment and monitoring of surface deformations following major seismic events. This paper reports a methodology for the assessment of surface deformations of viaducts by reducing drastically computational time. To this purpose, a multi-stage automatic bridge monitoring protocol is developed at the network level by integration of information into Geographic Information System (GIS) catalogues and use of the InSAR imagery technique. The first stage locates the viaducts in the area of interest by querying open data and inputting results into a GIS catalogue. On a second stage, an InSAR analysis of the identified bridges is performed. This approach allows an estimate of surface displacements as well as an identification of bridge areas affected by millimeter-scale settlements. Fundamental theoretical and working principles of the two methodologies are first introduced in the paper. Advantages against drawbacks of each technique are then discussed. The last Section reports a case study and a discussion of the main results including conclusions and future prospects.