Cranfield Defence and Security

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Browsing Cranfield Defence and Security by Supervisor "Andre, Daniel"

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    Bistatic SAR for Building Wall Material Characterisation
    (Cranfield University, 2020-07) Elgy, James; Andre, Daniel
    This thesis addresses the problem of using radar to extract interpretable information concerning both the structure and electrical properties of a wall, and the environment behind it. This is broken down into two subproblems: how to determine the thickness and electromagnetic properties of the wall without being in direct contact with it, and how to obtain the most accurate images of what lies beyond the wall. Existing research in the area is evaluated and a theoretical study is presented on the use of monostatic, bistatic, and multistatic Synthetic Aperture Radar (SAR) in both one and two dimensional apertures. New methods of determining the wall properties are evaluated by both computer simulation and with laboratory radar measurements, where a wall of concrete blocks is constructed. The robustness of the asymmetric SAR geometry approach is evaluated with the addition of complex objects placed behind the wall. The uncertainty associated with estimating the wall properties is evaluated and consequential improvements to image quality are discussed. It was found that an asymmetric bistatic SAR geometry accurately extracts the refractive index and thickness of a wall. The method is applicable to both cluttered environments and non-parallel wall trajectories without loss of accuracy. Applying a compensation for refraction in the SAR imagery results in better positional accuracy but does not necessarily result in better image focusing. Volumetric multistatic image formation benefits from applied refraction compensation. SAR image formation, and in particular volumetric image formation, can be significantly accelerated via a spatially variant basebanding technique followed by zero padding. Spatially variant basebanding is sub optimal when applied to a Through-Wall radar scenario where there is a visible wall signature in the image. Keywords: Through-Wall radar, Multistatic radar, Multidimensional signal processing, Electromagnetic propagation, Radar imagin
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    Remote intelligence of building interiors, using synthetic aperture radar
    (2020-06) Corbett, Brandon; Andre, Daniel
    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.
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    Subsurface radar imaging from space
    (Cranfield University, 2018) Edwards-Smith, A. J.; Andre, Daniel; Morrison, Keith
    Ground Penetrating Radar (GPR) and Synthetic Aperture Radar (SAR) are two widely used techniques for acquiring radar images. GPR, as its name suggests, produces radar images of the below ground environment. SAR is a remote sensing technique which allows moving radar systems to produce radar images with dramatically improved resolutions over conventional radar systems. Despite their benefits, both GPR and SAR suffer from certain limitations. In the case of GPR, the radar system has to be in close proximity with the subsurface volume being surveyed, which limits the process to relatively small areas that are easily accessible. SAR allows large areas to be surveyed rapidly from large distances, but cannot distinguish buried objects from surface objects. This thesis focuses on a radar technique that offers the opportunity to overcome these limitations and allow subsurface radar imaging of large areas using radar data gathered by remote sensing systems. This novel technique is known as Virtual Bandwidth SAR (VB-SAR). VB-SAR utilises changes in soil moisture over a series of SAR images to differentiate buried objects from objects on the surface. In addition to this differentiation, VB-SAR also allows extremely high (centimetre scale) subsurface range resolutions to be obtained from SAR images with range resolutions measured in metres. This research has experimentally demonstrated the basic feasibility of performing remote subsurface radar imaging with the VB-SAR scheme. Within the laboratory environment a buried target has been successfully imaged using VB-SAR and the fundamentals of VB-SAR have been verified. Dramatic increases in subsurface range resolutions have been demonstrated, as has the ability of the VB-SAR scheme to work correctly over a range of radar frequencies, observation angles and polarisations. This laboratory work has been enabled by use of the Tomographic Profiling (TP) imaging scheme. TP is a synthetic aperture based imaging algorithm, but unlike conventional SAR TP produces images with a constant look angle over the entire imaging scene. This enabled the performance of the VB-SAR imaging scheme to be easily evaluated over a range of look angles using a single radar dataset and simplified the experimental setup. In addition to the experimental work, simulation exercises have been conducted and image processors have been implemented. Simulation, using a simulator created as part of this work, has allowed testing of the VB-SAR scheme in a range of scenarios (sidelooking SAR, different soils, multiple buried targets). The image processor work has implemented a high performance TP processor and a practical VB-SAR imager.
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