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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.

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Approved for public release; distribution in unlimited. / An imaging radar, like ISAR, offers a combatant the capability to perform long range surveillance with high quality imagery for positive target identification. Extending this attractive feature to the battle damage assessment problem (BDA) gives the operator instant viewing of the target's behavior when it is hit. As a consequence, immediate and decisive action can be quickly taken (if required). However, the conventional Fourier processing adopted by most ISAR systems does not provide adequate time resolution to capture the target's dynamic responses during the hit. As a result, the radar image becomes distorted. To improve the time resolution, time-frequency transform (TFT) methods of ISAR imaging have been proposed. Unlike traditional Fourier-based processing, TFT's allows variable time resolution of the entire event that falls within the ISAR coherent integration period to be extracted as part of the imaging process. We have shown in this thesis that the use of linear Short Time-Frequency Transforms allows the translational response of the aircraft caused by a blast force to be clearly extracted. The TFT extracted images not only tell us how the aircraft responds to a blast effect but also provides additional information about the cause of image distortion in the traditional ISAR display.

Wireless sensor networks (WSN) have thus far been used for detection and tracking of static and mobile targets for surveillance and security applications. However, detection and tracking do not suffice for a complete satisfaction of these applications and an accurate target classification. To address this need, among various target classification methods, imaging of target yields the most valuable information. Nevertheless, imaging of mobile targets moving over an area requires networked and collaborative detection, tracking and imaging capabilities. With this regard, ultra-wideband (UWB) radar technology stands as a promising approach for networked target imaging over an area due to its unique features such as having no line-of-sight (LoS). However, the UWB wireless radar sensor network (WRSN) is yet to be developed for high quality imaging of mobile targets. In this thesis, an architecture for UWB wireless radar sensor network and a new collaborative mobile target imaging (CMTI) algorithm for UWB wireless radar sensor networks (WRSN) are presented. It is intended to accurately and efficiently obtain an image of mobile targets based on the collaborative eort of deployed UWB wireless radar sensor nodes. CMTI enables detection, tracking and imaging of mobile targets with a complete WRSN solution. CMTI exploits mobility of the target in the sensor field to build its own multi-static radar aperture. Performance evaluations reveal that CMTI obtains high quality radar image of mobile targets in WRSN with very low communication overhead and energy expenditure.

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Aim of PhD research is to exploit SAR Polarimetry technique for the identification of surface and subsurface archaeological features in the site of Gebel Barkal (Sudan), inscribed in the UNESCO World Heritage List since 2003. Sand penetration capability of both C-band and L-band sensors are discussed analysing archived ALOS PALSAR and RADARSAT-2 specifically acquired (2012-2013) images. Moreover, the research activity illustrates the potential of integrating SAR polarimetric and optical satellite data in a dedicated GIS project, realised in collaboration with the Universities of Turin and Venice (Italy). The monitoring of ancient sites by means of remotely acquired polarimetric SAR data represents a benefit for the archaeological research, where detected anomalies can address archaeological excavations or ground truth verification, as shown in the PhD dissertation, and where threatening factors affect the integrity of a cultural site.