Literatura académica sobre el tema "Ground based interferometric radar, ground based synthetic aperture radar, GB-SAR"

Ground-Based SAR Interferometry (GB-InSAR) is nowadays a proven technique widely used for slope monitoring in open pit mines and landslide control. Traditional GB-InSAR techniques involve transmitting and receiving antennas moving on a scanner to achieve the desired synthetic aperture. Mechanical movement limits the acquisition speed of the SAR image. There is a need for faster acquisition time as it plays an important role in correcting rapidly varying atmospheric effects. Also, a fast imaging radar can extend the applications to the measurement of vibrations of large structures. Furthermore, the mechanical assembly put constraints on the transportability and weight of the system. To overcome these limitations an electronically switched array would be preferable, which however faces enormous technological and cost difficulties associated to the large number of array elements needed. Imaging Multiple-Input Multiple Output (MIMO) radars can be used as a significant alternative to usual mechanical SAR and full array systems. This paper describes the ground-based X-band MIMO radar SPARX recently developed by IDS GeoRadar in order to overcome the limits of IDS GeoRadar’s well-established ground based interferometric SAR systems. The SPARX array consists of 16 transmit and 16 receive antennas, organized in independent sub-modules and geometrically arranged in order to synthesize an equally spaced virtual array of 256 elements.

Ground-based radar interferometry, which can be specifically classified as ground-based synthetic aperture radar (GB-SAR) and ground-based real aperture radar (GB-RAR), was applied to monitor the Liusha Peninsula landslide and Baishazhou Yangtze River Bridge. The GB-SAR technique enabled us to obtain the daily displacement evolution of the landslide, with a maximum cumulative displacement of 20 mm in the 13-day observation period. The virtual reality-based panoramic technology (VRP) was introduced to illustrate the displacement evolutions intuitively and facilitate the following web-based panoramic image browsing. We applied GB-RAR to extract the operational modes of the large bridge and compared them with the global positioning system (GPS) measurement. Through full-scale test and time-frequency result analysis from two totally different monitoring methods, this paper emphasized the 3-D display potentiality by combining the GB-SAR results with VRP, and focused on the detection of multi-order resonance frequencies, as well as the configure improvement of ground-based radars in bridge health monitoring.

Interferometric radars are widely used for static and dynamic monitoring of large structures such as bridges, culverts, wind turbine towers, chimneys, masonry towers, stay cables, buildings, and monuments. Most of these radars operate in Ku-band (17 GHz). Nevertheless, a higher operative frequency could allow the design of smaller, lighter, and faster equipment. In this paper, a fast MIMO-GBSAR (Multiple-Input Multiple-Output Ground-Based Synthetic Aperture Radar) operating in W-band (77 GHz) has been proposed. The radar can complete a scan in less than 8 s. Furthermore, as its overall dimension is smaller than 230 mm, it can be easily fixed to the head of a camera tripod, which makes its deployment in the field very easy, even by a single operator. The performance of this radar was tested in a controlled environment and in a realistic case study.

An integrated sensor system comprised of a terrestrial laser scanner (TLS), corner reflectors (CRs), and high precision linear rail is utilized to validate ground-based synthetic aperture radar (GB-SAR) interferometric micro-displacement measurements. A rail with positioning accuracy of 0.1 mm is deployed to ensure accurate and controllable deformation. The rail is equipped with a CR on a sliding platform for mobility. Three smaller CRs are installed nearby, each with a reflective sticker attached to the CR’s vertex; the CRs present as high-amplitude points both in the GB-SAR images and the TLS point cloud to allow for accurate data matching. We analyze the GB-SAR zero-baseline repeated rail differential interferometry signal model to obtain 2D interferograms of the test site in time series, and then use TLS to obtain a 3D surface model. The model is matched with interferograms to produce more intuitive 3D products. The CR displacements can also be extracted via surface reconstruction algorithm. Finally, we compared the rail sensor measurement and TLS results to optimize coherent scatterer selection and filter the data. The proposed method yields accurate target displacement results via quantitative analysis of GB-SAR interferometry.

Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.

Ground-based synthetic aperture radar (GB-SAR) uses active microwave remote-sensing observation mode to achieve two-dimensional deformation measurement and deformation trend extraction, which shows great prospects in the field of deformation monitoring. However, in the process of GB-SAR deformation monitoring, the disturbances caused by atmospheric effect cannot be neglected, and the atmospheric phases will seriously affect the precision of deformation monitoring. In discontinuous GB-SAR deformation monitoring mode, the atmospheric phases are particularly affected by changes of time and space, so the traditional models of atmospheric phase correction are no longer applicable. In this paper, the interferometric phase signal model considering atmospheric phase is first established. Then, the time- and space-varying characteristics of the atmospheric phase are analyzed, and a novel time- and space-varying atmospheric phase correction algorithm, based on coherent scatterers analysis, is proposed. Finally, slope deformation monitoring experiments are carried out to verify the validity and robustness of the proposed algorithm.

The Ground-Based SAR (GBSAR) is a terrestrial remote sensing technique used to measure and monitor deformation. In this paper we describe two complementary approaches to derive deformation measurements using GBSAR data. The first approach is based on radar interferometry, while the second one exploits the GBSAR amplitude. In this paper we consider the so-called discontinuous GBSAR acquisition mode. The interferometric process is not always straightforward: it requires appropriate data processing and analysis tools. One of the main critical steps is phase unwrapping, which can critically affect the deformation measurements. In this paper we describe the procedure used at the CTTC to process and analyse discontinuous GBSAR data. In the second part of the paper we describe the approach based on GBSAR amplitude images and an image-matching method.

Interferometric baseline estimation is a key procedure of interferometric synthetic aperture radar (SAR) data processing. The error of the interferometric baseline affects not only the removal of the flat-earth phase, but also the transformation coefficient between the topographic phase and elevation, which will affect the topographic phase removal for differential interferometric SAR (D-InSAR) and the accuracy of the final generated digital elevation model (DEM) product for interferometric synthetic aperture (InSAR). To obtain a highly accurate interferometric baseline, this paper firstly investigates the geometry of InSAR imaging and establishes a rigorous relationship between the interferometric baseline and the flat-earth phase. Then, a baseline refinement method without a ground control point (GCP) is proposed, where a relevant theoretical model and resolving method are developed. Synthetic and real SAR datasets are used in the experiments, and a comparison with the conventional least-square (LS) baseline refinement method is made. The results demonstrate that the proposed method exhibits an obvious improvement over the conventional LS method, with percentages of up to 51.5% in the cross-track direction. Therefore, the proposed method is effective and advantageous.

Abstract. This work addresses a methodology based on the Interferometric Synthetic Aperture Radar (InSAR) to analyse and monitor ground motion phenomena induced by underground mining activities, in the Legnica-Glogow Copper District, south-western Poland. Two stacks of ascending and descending Sentinel-1 Synthetic Aperture Radar (SAR) images are processed with a small baseline multitemporal approach. A simple method to select interferograms with high coherence and eliminated images with low redundancy is implemented to optimize the interferogram netwrork. The estimated displacement maps and time series show the effect of both linear and impulsive ground motion and are validated against Global Navigation Satellite System (GNSS) measurements.

The monitoring and early warning of a landslide in the reservoir area of a hydropower station are of great significance in the dam structure of the hydropower station and in the safety of people’s life and property on the reservoir bank. In this study, a new ground-based interferometric synthetic aperture radar system LKR-05-KU-S100 was used to carry out field monitoring tests on Lagu landslide and Xiaozhaju landslide of Dahuaqiao hydropower station and No. 1 landslide on the left bank of Xiaowan hydropower station on the Lancang river. The results show that, during the monitoring period, Lagu landslide of Dahuaqiao hydropower station and No. 1 landslide on the left bank of Xiaowan hydropower station are basically stable, and the deformation trend of Xiaozhaju landslide is obvious so it should undergo continuous monitoring. At the same time, the field monitoring test also shows that the new ground-based interferometric synthetic aperture radar system LKR-05-KU-S100 has the advantages of high precision and long-distance, all-day, all-weather, and large-scale monitoring and has unique advantages and broad application prospects for the overall deformation monitoring of large landslides in the reservoir area.

Le tecniche Multi-temporali SAR interferometriche (Mt-InSAR) rappresentano oggigiorno strumenti consolidati per mappare l’evoluzione temporale dei fenomeni di deformazione del suolo Terrestre. Queste tecniche utilizzano congiuntamente sets di interferogrammi SAR differenziali al fine di estrarre la componente legata alla deformazione e produrre così serie storiche di deformazione dei bersagli osservati dal sensore. L'affidabilità delle misure prodotte utilizzando algoritmi Mt-InSAR è strettamente legata alla capacità degli stessi algoritmi nell’isolare esclusivamente i segnali legati alla deformazione dal segnale complessivo interferometrico, e questa operazione diventa sempre più complessa all’aumentare dei livelli di rumore in ciascun interferogramma SAR coinvolto. Le tecniche Mt-InSAR canoniche sono altamente affidabili nel monitorare l'evoluzione dello spostamento dei target che risultano essere ampiamente stabili o coerenti per tutto il periodo di analisi. Diversamente, quando i bersagli sono particolarmente affetti da problemi di decorrelazione, le stime di deformazione ottenute risultano corrotte e inaffidabili. Questo pone le basi per lo sviluppo di processori Mt-InSAR avanzati che possano fornire stime accurate della deformazione del suolo anche in scenari con problemi di decorrelazione più o meno severi. In questo lavoro di tesi affronta dapprima lo studio dello stato dell’arte delle tecniche Mt-InSAR canoniche applicabili sia nel caso di piattaforme satellitare che terrestri, e dopodiché si propongono delle nuove tecniche Mt-InSAR per superare alcune delle criticità riscontrante. In particolare si studiano le tecniche convenzionali Mt-InSAR multigriglia per l'analisi dei target alla griglia di risoluzione spaziale più risoluta, evidenziandone le loro criticità in aree a media e bassa coerenza, e proprio in questo ambito è proposta una tecnica innovativa per meglio operare in ambienti decorrelati. Il metodo proposto si basa su efficienti operazioni con cui viene srotolata la fase (PhU) interferometrica eseguite alle scale spaziali native, ed in particolare, si srotolano dapprima gli interferogrammi alla scala di soluzione mediata (ML) attraverso algoritmi di PhU convenzionali (o avanzati). Successivamente, gli interferogrammi ML srotolati vengono utilizzati per facilitare le operazioni di PhU eseguite alla scala più fine (single-look). In dettaglio, gli interferogrammi multi-look srotolati vengono ricampionati alla griglia single-look e sottratti a modulo modulo-2π agli interferogrammi single-look. Gli interferogrammi epurati dai contributi a bassa frequenza vengono poi srotolati e aggiunti nuovamente agli interferogrammi multilook ricampionati alla griglia di risoluzione più fine. Per realizzare queste operazioni, a differenza dei metodi multigriglia canonici, non si utilizza alcun modello (lineare/non lineare) per recuperare le componenti di deformazione in alta frequenza. Infine, gli interferogrammi single-look srotolati sono opportunamente invertiti al fine di calcolare le serie storiche di deformazione del suolo attraverso un qualsiasi algoritmo a piccola baseline (SB) InSAR multi-temporale. I risultati sperimentali sono stati ottenuti elaborando una serie di dati SAR acquisiti dal sensore COSMO-SkyMed (banda X) sulla zona costiera di Shanghai, in Cina. La tesi prosegue analizzando le tecniche ai minimi quadrati pesate (WLS) e su come sono sfruttate nell’ambito InSAR al fine di migliorare l’operazione con cui si srotola la fase interferometrica e la generazione di serie storiche di deformazione. Proprio in questo contesto, utilizzando gli approcci WLS, si estende l'utilizzabilità dell'algoritmo Mt-InSAR Small BAseline Subset (SBAS) in aree caratterizzate da una coerenza spaziale medio-bassa. In particolare, pixel per pixel, si invertono esclusivamente le fasi interferometriche coerenti utilizzando una metrica a minimi quadrati pesati. Per cui attraverso una selezione adattiva, per ogni pixel si utilizzano ed invertono soltanto le fasi interferometriche coerenti, e tale caratterista può portare a diversi sottoinsiemi disgiunti di dati SAR, che sono poi invertiti sfruttando la Decomposizione a Valori Singolari Pesata (WSVD). Tuttavia, per taluni pixel, l’utilizzo esclusivo delle fasi interferometriche coerenti può portare in alcuni casi allo scarto di acquisizioni SAR particolarmente rumorose, il che si traduce in serie storiche di deformazione affidabili ma con campionamento temporale variabile. I risultati sperimentali sono stati condotti applicando la tecnica sviluppata ad un set di dati SAR acquisiti dai sensori COSMO-SkyMed (CSK) sulla regione Basilicata, nel sud Italia. Il lavoro di tesi continua analizzando le proprietà che ledono alla irrotazionalità delle triplette di fase di interferogrammi SAR multi-look. In particolare, si studiano le conseguenze delle incongruenze temporali di fase dei multi-look sulla generazione delle serie storiche di deformazione del suolo attraverso metodi SB Mt-InSAR. La ricerca condotta mostra come queste incongruenze di fase si possono propagare attraverso una rete temporale ridondante di interferogrammi SB, ed insieme agli errori di PhU, pregiudicano la qualità dei prodotti InSAR generati. In letteratura questo effetto va sotto il nome di bias di fase, il quale può pregiudicare l’affidabilità dei metodi SB quando si impostano delle soglie sulla massima baseline temporale troppo stringenti (nell’ordine di 30 giorni o meno). Proponiamo così, due nuovi metodi per la compensazione di tali fenomeni di bias, i quali metodi sono stati testati utilizzando dati SAR simulati e reali. I dati reali sono stati acquisiti dai sensori Sentinel-1A/B (banda C) sulle aree del Nevada (U.S.), e sulla zona del monte Etna in Sicilia, nel sud Italia. Dopo lo sviluppo di algoritmi per la parte satellitare, il lavoro si sposta sui sensori SAR terrestri (GB-SAR). In questo ambito proponiamo un metodo per stimare e compensare i disturbi introdotti dallo strato atmosferico (APS) in interferogrammi GB-SAR. Un’ambia analisi fisica, statistica e matematica dell'approccio presentato è fornita, discutendo inoltre le potenzialità e i limiti del metodo che a differenza di altri algoritmi, che stimano l'APS dai segnali di fase srotolati, nella metodologia proposta la compensazione avviene direttamente sul dato arrotolato, in modo tale che la stima non è affetta da nessun potenziale errore di PhU. Gli esperimenti eseguiti su dati InSAR GB-SAR simulati e reali confermano la validità della tecnica proposta, confermando inoltre che il metodo è vantaggioso nelle zone caratterizzate da una forte escursione di quota (come ad esempio nelle regioni Alpine e montuose). Infine, viene presentata un'applicazione SAR interferometrica per la stima delle deformazioni della superficie investigata in tre dimensioni (3-D) attraverso l'uso congiunto ed integrato di dati SAR acquisiti da piattaforme satellitari e terrestri. Più precisamente, la catena di combinazione interferometrica sviluppata si compone anche degli innovativi algoritmi Mt-InSAR sviluppati in questo lavoro di tesi, al fine di ottenere mappe di velocità media di deformazione 3-D direttamente alla griglia spaziale più risoluta possibile. Inoltre, in conclusione, vengono menzionate anche alcune interessanti applicazioni SAR satellitari in ambito di prevenzione ed analisi di particolari fenomeni naturali e indotti dall'uomo.
Multi-temporal SAR interferometric (Mt-InSAR) techniques are nowadays mature tools to measure the temporal evolution of the Earth’s surface with millimetric accuracy. The reliability of crustal measurements is closely related to the goodness of the used Mt-InSAR algorithms in isolating the deformation-related signal from the overall signal, and this becomes increasingly complex as the noise levels of each interferogram increase. Canonical techniques are highly reliable in monitoring the displacement evolution of targets that are found to be largely stable or coherent over the entire period of analysis. Otherwise, when the scatterers are particularly affected by decorrelation problems, the obtained deformation estimates turn out to be corrupted and unreliable. Thus, there is a strong demand for new advanced Mt-InSAR processors that can provide accurate estimates of crustal deformation even in scenarios with more or less severe decorrelation problems. This thesis work focuses on the study of multi-temporal InSAR techniques applicable in both satellite and terrestrial case. Specifically, the canonical Mt-InSAR multigrid techniques for analyzing targets at the finest resolution grid will be discussed extensively highlighting their criticality in medium to low coherence areas, and in this context an innovative technique is proposed to better operate in decorrelated environments. The new method relies on efficient phase-unwrapping (PhU) operations performed at the native spatial scales. In particular, a set of multi-look (ML) interferograms is first unwrapped using conventional (or advanced) PhU algorithms at the regional scale. Subsequently, ML unwrapped interferograms are used to facilitate the PhU operations performed at the local scale (single-look). Specifically, the unwrapped multi-look interferograms are resampled to the single-look grid and modulo-2π subtracted to the single-look interferograms. These phase residuals are then unwrapped and added back to the multi-look resampled interferograms. To accomplish these operations, at variance with alternative multiscale methods, no (linear/nonlinear) models are used to fit the spatial high-pass phase residuals. Finally, the unwrapped single-look interferograms are properly inverted to retrieve the ground displacement time series using any small baseline (SB)-oriented multitemporal InSAR tool. Experimental results are performed by processing a set of SAR data acquired by the X-band COSMO-SkyMed sensor over the coastal area of Shanghai, China. Then, the focusing moves on the Weighted Least-squares (WLS) techniques applied within the InSAR framework for improving the performance of the phase unwrapping operations as well as for better conveying the inversion of sequences of unwrapped interferograms to generate ground displacement maps. In both cases, the identification of low-coherent areas, where the standard deviation of the phase is high, is requested. Therefore, a WLS method that extends the usability of the Mt-InSAR Small BAseline Subset (SBAS) algorithm in regions with medium-to-low coherence is presented. In particular, the proposed method relies on the adaptive selection and exploitation, pixel-by-pixel, of the medium-to-high coherent interferograms, only, so as to discard the noisy phase measurements. The selected interferometric phase values are then inverted by solving a WLS optimization problem. Noteworthy, the adopted, pixel-dependent selection of the “good” interferograms to be inverted may lead the available SAR data to be grouped into several disjointed subsets, which are then connected, exploiting the Weighted Singular Value Decomposition (WSVD) method. However, in some critical noisy regions, it may also happen that discarding of the incoherent interferograms may lead to rejecting some SAR acquisitions from the generated ground displacement time-series, at the cost of the reduced temporal sampling of the data measurements. Thus, variable-length ground displacement time-series are generated. The presented experiments have been carried out by applying the developed technique to a SAR dataset acquired by the COSMO-SkyMed (CSK) sensors over the Basilicata region, Southern Italy. In the continuation of the thesis work, the properties characterizing the phase non-closure of multi-look SAR interferograms are explored. Precisely, we study the implications of multi-look phase time incongruences on the generation of ground displacement time-series through SB Mt-InSAR methods. Our research clarifies how these phase inconsistencies can propagate through a time-redundant network of SB interferograms and contribute, along with PhU errors, to the quality of the generated ground displacement products. Moreover, we analyze the effects of short-lived phase bias signals that could happen in sequences of short baseline interferograms and propose a strategy for their mitigation. The developed methods have been tested using both simulated and real SAR data. The latter were collected by the Sentinel-1A/B (C-band) sensors over the study areas of Nevada state, U.S., and Sicily Island, Italy. After the development of algorithms for the satellite part, the work veers to ground-based SAR (GB-SAR) sensors. In this field, we propose a method for estimating and compensating the atmospheric phase screen (APS) in sets of SAR interferograms generated with a GB-SAR instrument. We address the presented approach’s physical, statistical, and mathematical framework by discussing its potential and limitations. In contrast with other existing algorithms that estimate the APS from the unwrapped phase signals, our methodology is based on the straightforward analysis of the wrapped phases, directly. Therefore, the method is not affected by any potential phase unwrapping mistake, and it is suitable for Mt-InSAR applications. The effects of the local topography, the decorrelation noise, and the ground deformation on the APS estimates are deeply studied. Experiments performed on simulated and real GB-SAR InSAR data corroborate the validity of the theory. In particular, the simulated results show that the method is beneficial in zones with medium-to-high topographic slopes (e.g., for Alpine and mountainous regions). Further, an interferometric SAR application for the study of three-dimensional (3-D) deformation through the joint and integrated use of satellite and ground SAR data is presented. More precisely, the interferometric data-combining technique exploits the innovative Mt-InSAR algorithms mentioned above, and allows obtaining 3-D mean displacement velocity maps at the finest spatial grid among the available data. In conclusion, also some interested satellite SAR applications in prevention and analysis of particular natural and human-induced disasters are given.

This thesis works through the design of a radar-based system for imaging snowpacks remotely and over large areas to assist in avalanche prediction. The key to such a system is the ability to image volumes of snow at shallow, spatially-varying angles of incidence. To achieve this prerequisite, the design calls for a ground-based Synthetic Aperture Radar (SAR) capable of generating three-dimensional, ultra-high-resolution images of a snowpack. To arrive at design parameters for this SAR, the thesis works through relevant principles in avalanche mechanics, alpine-snowpack geophysics, and electromagnetic scattering theory. The thesis also works through principles of radar, SAR, antenna, and image processing theory to this end. A preliminary system is implemented to test the feasibility of the overall design. The preliminary system demonstrates ultra-high-resolution, three-dimensional imaging capabilities and the ability to image the volume of multiple alpine snowpacks. Images of these snowpacks display the structural patterns indicative of different layers in the snowpacks. Possible attributions of the patterns to physical properties in the snowpack are explored, but conclusions are not arrived at. Finally, lessons from the implementation of this preliminary system are discussed in terms of opportunities to be capitalized upon and problems to be overcome in future systems that more faithfully realize the complete design set forth in the thesis.

This thesis presents the development of a high-resolution ground-based 3D-SAR system and investigates its application to microwave-vegetation studies. The development process of the system is detailed including an enumeration of high-level requirements, discussions on key design issues, and detailed descriptions of the system down to a component level. The system operates on a 5.4 GHz (C-band) signal, provides a synthetic aperture area of 1.7 m x 1.7 m, and offers resolution of 0.75 m x 0.3 m x 0.3 m (range x azimuth x elevation). The system is employed on several trees with varying physical characteristics. The resulting imagery demonstrates successful 3D reconstruction of the trees and some of their internal features. The individual leaves and small branches are not visible due to the system resolution and the size of the wavelength. The foliage's outline and internal density distribution is resolved. Large branches are visible where geometry is favorable. Trunks are always visible due to their size and normal-facing incidence surface and their return has the strongest contribution from their base. The imagery is analyzed for dependencies on radar and tree parameters including: incidence angle, signal frequency, polarization, inclusion size, water content, and species. In the current work, a single frequency (5.4 GHz) and polarization (HH) is used which leaves the door open for future analysis to use other frequencies and polarizations. The improved resolution capabilities of the 3D-SAR system enables more precise backscatter measurements leading to a greater understanding of microwave-vegetation scattering behavior.

Ground-based/terrestrial radar interferometry (GBRI) is a scientific topic of increasing interest in recent years. The GBRI is used in several field as remote sensing technique for monitoring natural environment (landslides, glacier, and mines) or infrastructures (bridges, towers). These sensors provide the displacement of targets by measuring the phase difference between sending and receiving radar signal. If the acquisition rate is enough the GBRI can provide the natural frequency, e.g. by calculating the Fourier transform of displacement. The research activity, presented in this thesis, concerns design and development of some advanced GBRI systems. These systems are related to the following issue: detection of displacement vector, Multiple Input Multiple Output (MIMO) and radars with 3D capability. The conventional GBRI measures only the component of displacement along range direction. A GBRI operating in monostatic and bistatic modality is presented in this thesis. The sensor detects the first component of displacement as the conventional GBRI (monostatic) and an additional component through a transponder (bistatic). The radar has been successfully tested in controlled environment using a basic transponder (two antennas and an amplifier). The transponder has been improved to increase the gain of the amplifier and to solve some issue of the basic version. Finally, the system is used in real application for measuring the natural axis of a telecommunication tower. The most advanced GRBI system can measure the directional of arrival of scattered signal by exploiting the movement of the antenna on an axis (Ground Based Synthetic Aperture Radar - GBSAR). The step between two position on the axis has to be smaller than a quarter of wavelength. The emerging Multiple Input Multiple Output (MIMO) technique can be used to reduce the mechanical movement parts and the problems related to these. Also, for MIMO radar the spacing between two closer phase center has to be smaller than a quarter of wavelength for the Shannon theorem. In this thesis a Compressive Sensing (CS) MIMO radar is described. Indeed, the CS is a technique able to reconstruct signal without the constrain of Shannon theorem. The signal has to be sparse and randomly sampled in order to use the CS. The CS technique can be applied for increase the scan-length of a MIMO system of $40%div50%$. Therefore, by using the same number of antennas, the CS allows to increase the angular resolution of a MIMO radar. A prototype of interferometric CS MIMO radar has been developed and tested on some bridges. The results were compared with a conventional GBRI with a good agreement. The CS MIMO radar was able to discriminate the left-right movement of bridges. Unfortunately, the repetition rate of this prototype was not enough to retrieve the spectra of natural frequency. Since the movement is along a single axis the obtained radar image does not have angular resolution in the plane orthogonal to the scan axis. In other words, if the radar head scans along the x-axis the radar image cannot have resolution in elevation angle. This is not a serious problem when the scenario is a slope, where the elevation (z-axis) can be reasonably considered an unambiguous function of the (x,y) position. Unfortunately, there are cases where the geometry of the structure under test is much more complex, i.e in urban environment. In this thesis two radar systems with three-dimensional resolution are reported. These two systems synthesize the two technique previously described. Indeed, the first sensor uses the bistatic principle by exploiting the movement of an additional antenna in vertical axis for obtaining the resolution in elevation. The second system exploits the movement on a horizontal axis of the CS MIMO with phase center positioned on a vertical axis. In order to test the capability, the two radars were located in an urban scenario in front of a 7-storey building. Both systems were able to provide a 3D image of the building.

In chapter 1: The concept of the radar system has been introduced based on the radar block diagram. Moreover, there are some discussions about the radar equation, radar classification, and frequency of radar. In chapter 2: The fundamentals of radar cross-section are presented. Afterward, the RCS of two quadcopters is estimated by Electromagnetic Simulation Software (FEKO). In order to confirm the simulation, real measurement results are performed. Inverse synthetic radar (ISAR) processing are provided. In chapter 3: 2D And 3D inverse synthetic aperture radar (ISAR) image processing has been carried out for imaging small UAVs. The two-dimensional (2D) ISAR image is made by collecting scattered fields from different angles, while a 3D image can be obtained by integrating backscatter data in two spatial coordinates of the 2D aperture (cross-range in azimuth and elevation). Another topic that has been introduced is windowing in ISAR. In Synthetic Aperture Radar (SAR) processing the windowing in range and cross-range is a standard and its aim is to reduce the side-lobes of the Point Spread Function. In ISAR, when the rotation is smaller than 180°, the aperture windowing does not cause any estimation problems; it works exactly like a standard SAR. Problems occur when the rotation angle exceeds than 180° and especially when the rotation is complete. Therefore, for improving cross-range resolution in ISAR a new technique has been proposed. The rotation circle should be divided into four arcs of 180° before the focusing process, and a Kaiser window is applied on the chords of each of the arcs separately. Finally, the four resulting images are combined into one image as a radar image. In chapter 4: A new GBSAR system has been presented capable of generating both monostatic and bistatic images. Whereas the bistatic images need several hours to prepare the 3D information, the monostatic images are acquired in a few minutes by providing only 2D information about the targets in its field of view. Accordingly, the 3D measurement in conventional SAR radars is a computationally complex and time-consuming process but they can be interesting when the radar is used to image in a complex scenario. Due to this structure, it is able to create two images taken from different points of view with respect to the antenna system along an x-axis and the second channel along the z-axis. An advantage of proposed radar is that it can be operated as 2D interferometric radar for each horizontal scan, moreover, by varying the second channel height the 3D images are produced. It is worth mentioning that as a 3D image is obtained in bistatic condition, the angular resolution is worse with respect to a monostatic radar that scans a plan. In chapter 5: All concepts of compressive sensing have been discussed. The main bases and recovery methods are presented. Finally, the use of the CS algorithm in scenarios is carried out based on three different data. The first test is carried out with a corner reflector (CR) in front of the radar, the second one is performed with a seven-story building like the target, and the last one is accomplished in a natural scenario which was conducted with the "Belvedere Glacier" located on Italian Alpine.

This paper describes the first results of the European Ground Motion Service (EGMS). The EGMS is part of the Copernicus Land Monitoring Service and represents a unique initiative for performing ground deformation monitoring at a European scale. This service makes use of Advanced Differential Interferometric SAR (A-DInSAR) techniques based on satellite Synthetic Aperture Radar (SAR) imagery. In particular, it exploits the Sentinel-1A/B SAR images of the Copernicus Programme, acquired over Europe. The paper briefly summarizes the main characteristics of the EGMS, describing different products of this Service. Then it presents some case studies extracted from the EGMS products. Examples of natural and human-induced geohazards are described.

TransCanada owns and operates over 38,000 km of pipeline throughout North America, which cross over 3,300 slopes and 1,200 watercourses. Ground movements on slopes at river crossings are an important pipeline hazard across Canada and especially within the Alberta system. These movements have led to several past pipeline ruptures and the development of a relatively extensive slope monitoring program. Historically, ground movement impacts are an industry-wide problem. The results of a 1998 study by the Gas Research Institute reported that external force damage from natural forces, including ground movement, was responsible for approximately 12 percent of all incidents reported on U.S. onshore pipelines between 1985 and 1994. Of all natural force incidents, ground movement accounted for approximately 29 percent of the total, on average. Furthermore, of all fires or explosions resulting from pipeline incidents, ground movements were reported responsible for about 5 percent of the total. In a similar study of Alberta pipeline failures and incidents between 1980 and 1997 (EUB, 1998), ground movement was the cause of 56 ruptures, or 3.5 percent of the total. Until recently, monitoring of the progress of slope movements was reactive and undertaken in a traditional fashion, using primarily slope inclinometers and/or ground surveys. Recently, however, TransCanada has adopted a proactive approach for the management of ground movements. Consistent with the management of other pipeline hazards, such as corrosion, ground movements are cast in a risk-based framework. The application of DInSAR technology, Differential Interferometry applied to satellite synthetic aperture radar (SAR) imagery, fits well within the proactive approach and has proven successful in measuring ground movements on ROW slopes to sub-centimetre accuracy. In 2000, a Pipeline Research Committee International (PRCI) study was carried out on a TransCanada Right of Way (RoW) that compared conventional slope indicator readings with DInSAR technology and proved the capability of the technology. TransCanada has begun to use DInSAR technology in this program of monitoring Alberta slopes. Typically, TransCanada monitors slope movements at 53 sites with frequency of readings between bi-annually and 4 times per year using conventional methods. Since 2001, 14 slopes on the TransCanada system have been instrumented using DInSAR methods and monitoring of movements using interferometric methods is continuing.

When monitoring deformations in natural hazards such as rockfalls and landslides, the use of 3D models has become a standard. Several geomatic techniques allow the generation of these models. However, each one has its pros and cons regarding accuracy, cost, sample frequency, etc. In this contribution a fixed-location time lapse camera system for continuous rockfall monitoring using photogrammetry has been developed as an alternative to Light Detection and Ranging (LiDAR) and ground-based interferometric synthetic-aperture radar (GB-InSAR). The usage of stereo photogrammetry allows the obtention of 3D points clouds at a low cost and with a high sample frequency, essential to detect premonitory displacements. In this work the designed system consists of three digital single-lens reflex (DSLR) cameras which collect photographs of the rock slope daily controlled by a Raspberry Pi computer using the open-source library gPhoto2. Photographs are automatically uploaded to a server using 3G network for processing. This system was implemented at Castellfollit de la Roca village (Girona province, Spain), which sits on a basaltic cliff that has shown significant rockfall intensity in recent years. The 3D models obtained will allow monitoring rockfalls frequency, premonitory displacements, and calculate the erosion rate of the slope. All technical decisions taken for the design and implementation on this specific site are discussed and first results shown.