| Summary: | This thesis has tested the validity of the SubSAR technique for subsurface feature detection on a field-scale experiment using Synthetic Aperture Radar (SAR) satellite data. Most of the current SAR subsurface imaging approaches are based on analysing the amplitude component of the SAR images only, which is not sufficient by itself to determine whether an imaged object lies on the earth’s surface or it is beneath the surface. Thus, the current approaches usually require an additional source of information (e.g., optical imagery) to help interpret SAR images for subsurface feature detection.
A recent approach for subsurface detection, called SubSAR, utilises the amplitude information of the SAR image, as well as the DInSAR phase history, proved to be a promising method for discriminating between surface and buried features without requiring additional source of information. However, this method has only demonstrated in the lab. The overall aim of this thesis it to validate the SubSAR technique for application to satellite SAR data. Therefore, a field-scale experiment was designed, which extends the lab experiments into the field. This involves creating a set of radar point targets and covering them with a layer of sand to simulate buried targets. A set of measurements are then undertaken to test the validity and the quality of the experiment, involving the analysis of the radiometric and interferometric phase stability of the point targets. This is required to ensure that any change in the measured
phase and backscatter is due to the variations in the water content of the covering sand and not the instability of the radar point targets (the Corner Reflectors CRs). Lastly,
the SubSAR experiment itself is then implemented by monitoring the effect of the covering sand’s moisture content on the incident signal, including both the backscatter and the DInSAR phase.
Results of the experiments suggested that it is possible to apply the SubSAR technique for subsurface feature detection from satellite SAR data. It is also found that the
information obtained from the SAR data only can be used to detect buried features, without the need to an additional source of information, such as the soil moisture. This
is very important in real life applications, such as pipeline and landmines detection, where soil moisture measurements are probably unavailable.
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