Littérature scientifique sur le sujet « Ground-Based Synthetic Aperture Radar (GBSAR) »

Ground-based Synthetic Aperture Radar (GBSAR) is a tremendous example of the extended applications of Synthetic Aperture Radar (SAR). GBSAR is extremely useful in human-made structure observations, terrain mapping, landslide monitoring and many more. However, the process of designing and developing the GBSAR system is rather costly and time-consuming. It would be of a great advantage for system designers to have a realistic simulation and designing tool to anticipate the results before the implementation of the final design. In this paper, we are going to present the integrated simulation and designing tool that we have developed for a generic GBSAR system. We named it iSIM v2.0.

Ground-based Synthetic Aperture Radar (GBSAR) is a tremendous example of the extended applications of Synthetic Aperture Radar (SAR). GBSAR is extremely useful in human-made structure observations, terrain mapping, landslide monitoring and many more. However, the process of designing and developing the GBSAR system is rather costly and time-consuming. It would be of a great advantage for system designers to have a realistic simulation and designing tool to anticipate the results before the implementation of the final design. In this paper, we are going to present the integrated simulation and designing tool that we have developed for a generic GBSAR system. We named it iSIM v2.0

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.

Compressive sensing (CS) is a recent technique that promises to dramatically speed up the radar acquisition. Previous works have already tested CS for ground-based synthetic aperture radar (GBSAR) performing preliminary simulations or carrying out measurements in controlled environments. The aim of this article is a systematic study on the effective applicability of CS for GBSAR with data acquired in real scenarios: an urban environment (a seven-storey building), an open-pit mine, and a natural slope (a glacier in the Italian Alps). The authors tested the most popular sets of orthogonal functions (the so-called ‘basis’) and three different recovery methods (l1-minimization, l2-minimization, orthogonal pursuit matching). They found that Haar wavelets as orthogonal basis is a reasonable choice in most scenarios. Furthermore, they found that, for any tested basis and recovery method, the quality of images is very poor with less than 30% of data. They also found that the peak signal–noise ratio (PSNR) of the recovered images increases linearly of 2.4 dB for each 10% increase of data.

Abstract. This study demonstrates the interferometric processing experiments of our developed multiple-input multiple-output ground-based synthetic aperture radar (MIMO GBSAR) system. GBSAR systems are known as precise noncontact instruments for monitoring earth dynamics. In recent years W band MIMO radars have shown interesting potential in this field due to their low cost, compact size, and high phase sensitivity. MIMO capability enables the angular discrimination of multiple targets in the same range as the radar sensor. In our previous works, we developed a high-resolution MIMO GBSAR system based on the combination of MIMO radar and mechanical rail. Accordingly, this study investigates the developed system’s displacement monitoring capability by presenting a controlled experiment, using fixed and moving corner reflectors and gathering 36 time series of data. We compare and discuss the results obtained from MIMO GBSAR and MIMO radar configurations. The results show that our developed system highly agrees with MIMO radar’s interferometric measurements while providing a better target discrimination capability and higher signal noise ratio.

The features of the landslide geological disaster are wide distribution, variety, high frequency, high intensity, destructive and so on. It has become a natural disaster with harmful and wide range of influence. The technology of ground-based synthetic aperture radar is a novel deformation monitoring technology developed in recent years. The features of the technology are large monitoring area, high accuracy, long distance without contact and so on. In this paper, fast ground-based synthetic aperture radar (Fast-GBSAR) based on frequency modulated continuous wave (FMCW) system is used to collect the data of Ma Liuzui landslide in Chongqing. The device can reduce the atmospheric errors caused by rapidly changing environment. The landslide deformation can be monitored in severe weather conditions (for example, fog) by Fast-GBSAR with acquisition speed up to 5 seconds per time. The data of Ma Liuzui landslide in Chongqing are analyzed in this paper. The result verifies that the device can monitor landslide deformation under severe weather conditions.

Ground-based synthetic aperture radar (GBSAR) systems are popular remote sensing instruments for detecting the ground changes of landslides, glaciers, and open pits as well as for detecting small displacements of large structures, such as bridges and dams. Recently (2017), a novel mono/bistatic GBSAR configuration was proposed to acquire two different components of displacement of the targets in the field of view. This bistatic configuration relies on a transponder that consists—in its basic implementation—of just two antennas and an amplifier. The aim of this article was to design and experimentally test an improved transponder with cross-polarized antennas and frequency shifter that is able to prevent possible oscillations even at very high gain, as required in long-range applications. The transponder was successfully field-tested, and its measured gain was 91 dB gain.

Due to the high temporal resolution (e.g., 10 s) required, and large data volumes (e.g., 360 images per hour) that result, there remain significant issues in processing continuous ground-based synthetic aperture radar (GBSAR) data. This includes the delay in creating displacement maps, the cost of computational memory, and the loss of temporal evolution in the simultaneous processing of all data together. In this paper, a new processing chain for real-time GBSAR (RT-GBSAR) is proposed on the basis of the interferometric SAR small baseline subset concept, whereby GBSAR images are processed unit by unit. The outstanding issues have been resolved by the proposed RT-GBSAR chain with three notable features: (i) low requirement of computational memory; (ii) insights into the temporal evolution of surface movements through temporarily-coherent pixels; and (iii) real-time capability of processing a theoretically infinite number of images. The feasibility of the proposed RT-GBSAR chain is demonstrated through its application to both a fast-changing sand dune and a coastal cliff with submillimeter precision.

Ground-based arc-scanning synthetic aperture radar (ArcSAR) is the novel ground-based synthetic aperture radar (GBSAR). It scans 360-degree surrounding scenes by the antenna attached to rotating boom. Therefore, compared with linear scanning GBSAR, ArcSAR has larger field of view. Although the feasibility of ArcSAR has been verified in recent years, its imaging algorithm still presents difficulties. The imaging accuracy of ArcSAR is affected by terrain fluctuation. For rotating scanning ArcSAR, even if targets in scenes have the same range and Doppler with antenna, if the heights of targets are different, their range migration will be different. Traditional ArcSAR imaging algorithms achieve imaging on reference plane. The height difference between reference plane and target in scenes will cause the decrease of imaging quality or even image defocusing because the range migration cannot be compensated correctly. For obtaining high-precision ArcSAR image, we propose interferometric DEM (digital elevation model)-assisted high precision imaging method for ArcSAR. The interferometric ArcSAR is utilized to acquire DEM. With the assist of DEM, target in scenes can be imaged on its actual height. In this paper, we analyze the error caused by ArcSAR imaging on reference plane. The method of extracting DEM on ground range for assisted ArcSAR imaging is also given. Besides, DEM accuracy and deformation monitoring accuracy of proposed method are analyzed. The effectiveness of the proposed method was verified by experiments.

In this paper, aiming at the limitation of persistence scatterers (PS) points selection, a new method for selecting PS points has been introduced based on the average coherence coefficient, amplitude dispersion index, estimated signal-to-noise ratio and displacement standard deviation of multiple threshold optimization. The stability and quality of this method are better than that of a single model. In addition, an atmospheric correction model has also been proposed to estimate the atmospheric effects on Ground-based synthetic aperture radar (GBSAR) observations. After comparing the monitoring results before and after correction, we clearly found that the results are in good agreement with the actual observations after applying the proposed atmospheric correction approach.

This thesis describes a first hands-on experience working with a Ground-Based Synthetic Aperture Radar (GB-SAR) at the Institute of Geomatics in Castelldefels (Barcelona, Spain), used to exploit radar interferometry usually employed on space borne platforms. We describe the key concepts of a GB-SAR as well as the data processing procedure to obtain deformation measurements. A large part of the thesis work have been devoted to development of GB-SAR processing tools such as coherence and interferogram generation, automating the co-registration process, geocoding of GB-SAR data and the adaption of existing satellite SAR tools to GB-SAR data. Finally a series of field campaigns have been conducted to test the instrument in different environments to collect data necessary to develop GB-SAR processing tools as well as to discover capabilities and limitations of the instrument.   The key outcome of the field campaigns is that high coherence necessary to conduct interferometric measurements can be obtained with a long temporal baseline. Several factors that affect the result are discussed, such as the reflectivity of the observed scene, the image co-registration and the illuminating geometry.
Det här examensarbetet bygger på erfarenheter av arbete med en mark-baserad syntetisk apertur radar (GB-SAR) vid Geomatiska Institutet i Castelldefels (Barcelona, Spanien). SAR tekniken tillåter radar interferometri som är en vanligt förekommande teknik både på satellit och flygburna platformar. Det här arbetet beskriver instrumentets tekniska egenskaper samt behandlingen av data for att uppmäta deformationer. En stor del av arbetet har ägnats åt utveckling av GB-SAR data applikationer som koherens och interferogram beräkning, automatisering av bild matchning med skript, geokodning av GB-SAR data samt anpassning av befintliga SAR program till GB-SAR data. Slutligen har mätningar gjorts i fält for att samla in data nödvändiga for GB-SAR applikations utvecklingen samt få erfarenhet av instrumentets egenskaper och begränsningar.   Huvudresultatet av fältmätningarna är att hög koherens nödvändig för interferometriska mätningar går att uppnå med relativ lång tid mellan mätepokerna. Flera faktorer som påverkar resultatet diskuteras, som det observerade områdets reflektivitet, radar bild matchningen och den illuminerande geometrin.

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.

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 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.

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.

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.

碩士
元智大學
通訊工程學系
104
This thesis is based on space program at Yuan Ze University’s communication center. However, design of satellite-based Synthetic Aperture Radar(SAR) needs high power module and higher cost. So we design RF front-end module for C-band ground-based SAR which is lower band. It follows by SAR principle and we test all RF components for RF front-end transceiver. In addition, we design a module for C-band ground-based SAR combined with signal program which can transmit LFM pulse signal and signalprocessing. In the test, we slide the RF Front-End Module to observe atarget, and use notebook to capture the received signal from the scope stored for further SAR processing. Finally, we will analyze imaging correctness.

AbstractThis International Programme on Landslide (IPL) Project 202 paper presents a scalable remote piloted aircraft system (RPAS) platform that streamlines unoccupied aerial vehicle (UAV) flight operations for data capture, cloud processing and image rendering to inventory and monitor slow-moving landslides along the national railway transportation corridor in southwestern British Columbia, Canada. Merging UAV photogrammetry, ground-based real-time kinematic global navigation satellite system (RTK-GNSS) measurements, and satellite synthetic aperture radar interferometry (InSAR) datasets best characterizes the distribution, morphology and activity of landslides over time. Our study shows that epochal UAV photogrammetry, benchmarked with periodic ground-based RTK-GNSS measurements and satellite InSAR platforms with repeat visit times of weeks (e.g., RADARSAT-2 and SENTINEL-1) to days (e.g. RADARSAT Constellation Mission) provides rapid landslide monitoring capability with cm-scale precision and accuracy.

With the rapid socio-economic development in the past three decades, the pace of urban construction in Shenzhen has been accelerating, and the ground subsidence phenomenon in Shenzhen has been intensifying. The widespread ground subsidence in Shenzhen produces important hazards to the urban environment and important urban infrastructures, leading to disasters such as tilting and collapse of buildings, and back-up of seawater. In this paper, based on satellite synthetic aperture radar interferometry (InSAR) technology to obtain the overall subsidence information in Nanshan District, Shenzhen, we use high-precision laser point cloud, 3D building model and other data to monitor the specific subsidence information of buildings and carry out the risk assessment of housing buildings in Nanshan District to provide scientific decision-making basis for its subsidence cause analysis and prevention and control.