Remote intelligence of building interiors, using synthetic aperture radar - Corbett, Brandon (Cranfield University, 2020)
With most criminal and nefarious activity occurring underground or within buildings, intelligence gathering on the nature and activities of concealed areas is key for both defence and civilian sectors, leading to the formation of the “Remote Intelligence of Building Interiors” (RIBI) project. Synthetic aperture radar (SAR) systems have become fundamental in the remote sensing field, and their ability to complete inter-medium measurements makes them well suited for the RIBI project. Firstly, vibrating target phenomenology within buildings was investigated. If you can identify this phenomenon, you could infer the possibility of manufacturing equipment within the building. This topic presented several novel contributions to the field including an understanding of the localisation of vibrating target artefacts, a new experimental measurement methodology to capture this phenomenon, and the identification of a new multipath-vibration artefact. Following this a comprehensive analysis of the Bright-Sapphire II data-dome trials was conducted. This is a volumetric airborne SAR collection designed to allow for investigations into how different building types affect the detectability of targets positioned within them. An assessment of the SAR image quality across the full azimuthal and vertical extents was examined, revealing extensive radio frequency interference (RFI) and image alignment issues. This in turn reduced the overall quality and focusing of any SAR image produced from the data. To address these image alignment problems, the development of a new autofocus algorithm based on a hybrid map drift (MD) - prominent point processing (PPP) solution was completed. The solution was developed on simulated data and validated using AFRL’s Gotcha dataset. When applied to the Bright-Sapphire II dataset, the solution yielded successful results in improving scatterer alignment along the ground plane. However, volumetric imagery of the scene was not as successful. It was determined if one wants to unlock the full potential of the Bright-Sapphire II dataset, increasing the usable bandwidth will be key to accomplishing this, which will require resolving the challenging RFI contaminating the data.