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Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target with good fidelity. In the first part of this dissertation, a low-rank and sparse representation based approach is designed to remove the clutter produced by rough ground surface reflection for impulse radar. In the second part, Hilbert Transform and 2-D Renyi entropy based statistical analysis is explored to improve RoI detection efficiency and to reduce the computational cost for more sophisticated data post-processing. In the third part, a back-projection imaging algorithm is designed for both ground-coupled and air-coupled multistatic GPR configurations. Since the refraction phenomenon at the air-ground interface is considered and the spatial offsets between the transceiver antennas are compensated in this algorithm, the data points collected by receiver antennas in time domain can be accurately mapped back to the spatial domain and the targets can be imaged in the scene space under testing. Experimental results validate that the proposed three-stage cascade signal processing methodologies can improve the performance of GPR system.

The ASCE confers an overall D+ grade to American infrastructure, while the NAE lists the restoration and improvement of urban infrastructure as one of its grand engineering challenges for the 21st century, indicating that infrastructure renovation and development is a major challenge in the US. Furthermore, according to the UN World Urbanization Prospects, about 55% of the world's population lives in urban areas and this percentage is set to grow, especially in Africa and Asia. The growth of urban population poses challenges to the expansion of underground infrastructure, such as water, sewage, electricity and telecommunications. Localization and mapping of underground infrastructure are fundamental for infrastructure maintenance and development. Ground penetrating radar (GPR) is a remote sensing method capable of detecting subsurface assets that has been used in the localization and mapping of underground utilities. This thesis contributes improvements of GPR systems and imaging algorithms towards smarter infrastructure, specifically: Application of GPR imaging algorithm to improve GPR data readability and generate augmented reality (AR) content; Use of photogrammetric methods to improve GPR positioning for underground infrastructure localization and mapping.

Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target with good fidelity. In the first part of this dissertation, a low-rank and sparse representation based approach is designed to remove the clutter produced by rough ground surface reflection for impulse radar. In the second part, Hilbert Transform and 2-D Renyi entropy based statistical analysis is explored to improve RoI detection efficiency and to reduce the computational cost for more sophisticated data post-processing. In the third part, a back-projection imaging algorithm is designed for both ground-coupled and air-coupled multistatic GPR configurations. Since the refraction phenomenon at the air-ground interface is considered and the spatial offsets between the transceiver antennas are compensated in this algorithm, the data points collected by receiver antennas in time domain can be accurately mapped back to the spatial domain and the targets can be imaged in the scene space under testing. Experimental results validate that the proposed three-stage cascade signal processing methodologies can improve the performance of GPR system.

Synthetic Aperture Radar (SAR) is an emerging technique in remote sensing. The technology is capable of producing high-resolution images of the earth surface in all-weather conditions. Thesis work describes the present available methods for positioning and imaging targets using M-sequence UWB (Ultra-Wideband) radar signals with moving antennas and SAR algorithm to retrieve position and image of the target. M-sequence UWB radar technology used as signal source for transmission and receiving echoes of target. Pseudo random binary sequence is used as a transmitted signal. These radars have an ability to penetrate signal through natural and unnatural objects. It offers low cost and quality security system. Among a number of techniques of image retrieval in Synthetic Aperture Radar, study of Global back projection (GBP) algorithm is presented. As a time domain algorithm, GBP possesses inherent advantages over frequency domain algorithm like ability to handle long integration angle, wider bandwidth and unlimited aperture size. GBP breaks the full synthesis aperture into numbers of sub-apertures. These sub-apertures are treated pixel by pixel. Each sub-aperture is converted to a Cartesian image grid to form an image.  During this conversion the signal is treated with linear interpolation methods in order to achieve the best quality of the images. The objective of this thesis is the imaging of target using M-sequence UWB radar and processing SAR raw data using Global back projection algorithm.

[ES] La tomografía por emisión de positrones (PET, del inglés Positron Emission Tomography) es una técnica de medicina nuclear en la que se genera una imagen a partir de la detección de rayos gamma en coincidencia. Estos rayos son producidos dentro de un paciente al que se le inyecta una radiotrazador emisor de positrones, los cuales se aniquilan con electrones del medio circundante. El proceso de adquisición de eventos de interacción, tiene como unidad central el detector del escáner PET, el cual se compone a su vez de un cristal de centelleo, encargado de transformar los rayos gamma incidentes en fotones ópticos dentro del cristal. La finalidad es entonces, determinar las coordenadas de impacto dentro del cristal de centelleo con la mayor precisión posible, para que, a partir de dichos puntos, se pueda reconstruir una imagen. A lo largo de la historia, los detectores basados en cristales pixelados han representado la elección por excelencia para la la fabricación de escáneres PET. En está tesis se evalúa el impacto en la resolución espacial del escáner PET MINDView, desarrollado dentro del séptimo programa Marco de la Unión Europea No 603002, el cual se basa en el uso de cristales monolíticos. El uso de cristales monolíticos, facilita la determinación de la profundidad de interacción (DOI - del inglés Depth Of Interaction) de los rayos gamma incidentes, aumenta la precisión en las coordenadas de impacto determinadas, y disminuye el error de paralaje que se induce en cristales pixelados, debido a la dificultad para determinar la DOI. En esta tesis, hemos logrado dos objetivos principales relacionados con la medición de la resolución espacial del escáner MINDView: la adaptación del un algoritmo de STIR de Retroproyección Filtrada en 3D (FBP3DRP - del inglés Filtered BackProjection 3D Reproyected) a un escáner basado en cristales monolíticos y la implementación de un algoritmo de Retroproyección y filtrado a posteriori (BPF - BackProjection then Filtered). Respecto a la adaptación del algoritmo FBP, las resoluciones espaciales obtenidas varían en los intervalos [2 mm, 3,4 mm], [2,3 mm, 3,3 mm] y [2,2 mm, 2,3 mm] para las direcciones radial, tangencial y axial, respectivamente, en el primer prototipo del escáner MINDView dedicado a cerebro. Por otra parte, en la implementación del algoritmo de tipo BPF, se realizó una adquisición de un maniquí de derenzo y se comparó la resolución obtenida con el algoritmo de FBP y una implementación del algoritmo de subconjuntos ordenados en modo lista (LMOS - del inglés List Mode Ordered Subset). Mediante el algoritmo de tipo BPF se obtuvieron valores pico-valle de 2.4 a lo largo de los cilindros del maniquí de 1.6 mm de diámetro, en contraste con las medidas obtenidas de 1.34 y 1.44 para los algoritmos de FBP3DRP y LMOS, respectivamente. Lo anterior se traduce en que, mediante el algoritmo de tipo BPF, se logra mejorar la resolución para obtenerse un valor promedio 1.6 mm. / [CAT] La tomografia per emissió de positrons és una tècnica de medicina nuclear en la qual es genera una imatge a partir de la detecció de raigs gamma en coincidència. Aquests raigs són produïts dins d'un pacient a què se li injecta una radiotraçador emissor de positrons, els quals s'aniquilen amb electrons de l'medi circumdant. El procés de adquición d'esdeveniments d'interacció, té com a unitat central el detector de l'escàner PET, el qual es compon al seu torn d'un vidre de centelleig, encarregat de transformar els raigs gamma incidents en fotons òptics dins el vidre. La finalitat és llavors, determinar les coordenades d'impacte dins el vidre de centelleig amb la major precisió possible, perquè, a partir d'aquests punts, es pugui reconstruir una imatge. Al llarg de la història, els detectors basats en cristalls pixelats han representat l'elecció per excellència per a la la fabricació d'escàners PET. En aquesta tesi s'avalua l'impacte en la resolució espacial de l'escàner PET MINDView, desenvolupat dins el setè programa Marc de la Unió Europea No 603.002, el qual es basa en l'ús de vidres monolítics. L'ús de vidres monolítics, facilita la determinació de la profunditat d'interacció dels raigs gamma incidents, augmenta la precisió en les coordenades d'impacte determinades, i disminueix l'error de parallaxi que s'indueix en cristalls pixelats, a causa de la dificultat per determinar la DOI. En aquesta tesi, hem aconseguit dos objectius principals relacionats amb el mesurament de la resolució espacial de l'escàner MINDView: l'adaptació de l'un algoritme de STIR de Retroprojecció Filtrada en 3D a un escàner basat en cristalls monolítics i la implementació d'un algoritme de Retroprojecció i filtrat a posteriori. Pel que fa a l'adaptació de l'algoritme FBP3DRP, les resolucions espacials obtingudes varien en els intervals [2 mm, 3,4 mm], [2,3 mm, 3,3 mm] i [2,2 mm, 2,3 mm] per les direccions radial, tangencial i axial, respectivament, en el primer prototip de l'escàner MINDView dedicat a cervell. D'altra banda, en la implementació de l'algoritme de tipus BPF, es va realitzar una adquisició d'un maniquí de derenzo i es va comparar la resolució obtinguda amb l'algorisme de FBP3DRP i una implementació de l'algoritme de subconjunts ordenats en mode llista (LMOS - de l'anglès List Mode Ordered Subset). Mitjançant l'algoritme de tipus BPF es van obtenir valors pic-vall de 2.4 al llarg dels cilindres de l'maniquí de 1.6 mm de diàmetre, en contrast amb les mesures obtingudes de 1.34 i 1.44 per als algoritmes de FBP3DRP i LMOS, respectivament. L'anterior es tradueix en que, mitjançant l'algoritme de tipus BPF, s'aconsegueix millorar la resolució per obtenir-se un valor mitjà 1.6 mm. / [EN] Positron Emission Tomography (PET) is a medical imaging technique, in which an image is generated from the detection of gamma rays in coincidence. These rays are produced within a patient, who is injected with a positron emmiter radiotracer, from which positrons are annihilated with electrons in the media. The event acquisition process is focused on the scanner detector. The detector is in turn composed of a scintillation crystal, which transform the incident ray gamma into optical photons within the crystal. The purpose is then to determine the impact coordinates within the scintillation crystal with the greatest possible precision, so that, from these points, an image can be reconstructed. Throughout history, detectors based on pixelated crystals have represented the quintessential choice for PET scanners manufacture. This thesis evaluates the impact on the spatial resolution of the MINDView PET scanner, developed in the seventh Framework program of the European Union No. 603002, which detectors are based on monolithic crystals. The use of monolithic crystals facilitates the determination of the depth of interaction (DOI - Depth Of Interaction) of the incident gamma rays, increases the precision in the determined impact coordinates, and reduces the parallax error induces in pixelated crystals, due to the difficulties in determining DOI. In this thesis, we have achieved two main goals related to the measurement of the spatial resolution of the MINDView PET scanner: the adaptation of an STIR algorithm for Filtered BackProjection 3D Reproyected (FBP3DRP) to a scanner based on monolithic crystals, and the implementation of a BackProjection then Filtered algorithm (BPF). Regarding the FBP algorithm adaptation, we achieved resolutions ranging in the intervals [2 mm, 3.4 mm], [2.3 mm, 3.3 mm] and [2.2 mm, 2.3 mm] for the radial, tangential and axial directions, respectively. On the an acquisition of a derenzo phantom was performed to measure the spacial resolution, which was obtained using three reconstruction algorithms: the BPF-type algorithm, the FBP3DRP algorithm and an implementation of the list-mode ordered subsets algorithm (LMOS). Regarding the BPF-type algorithm, a peak-to-valley value of 2.4 were obtain along rod of 1.6 mm, in contrast to the measurements of 1.34 and 1.44 obtained for the FBP3DRP and LMOS algorithms, respectively. This means that, by means of the BPF-type algorithm, it is possible to improve the resolution to obtain an average value of 1.6 mm. / Sánchez Góez, S. (2020). Algoritmo de reconstrucción analítico para el escáner basado en cristales monolíticos MINDView [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/159259

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