Scalar imaging algorithms originally developed for the processing of remote sensing measurements (e.g., the synthetic-aperture radar method) or seismic reflection data (e.g., the Gazdag phase-shift method) are commonl...
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Scalar imaging algorithms originally developed for the processing of remote sensing measurements (e.g., the synthetic-aperture radar method) or seismic reflection data (e.g., the Gazdag phase-shift method) are commonly used for the processing of ground-penetrating radar (GPR) data. Unfortunately;these algorithms do not account for the radiation characteristics of GPR source and receiver antennas or the vectorial nature of radar waves. We present a new multicomponent imaging algorithm designed specifically for vector electromagnetic-wave propagation. It accounts for all propagation effects, including the vectorial characteristics of the source and receiver antennas and the polarization of the electromagnetic wavefield. A constant-offset source-receiver antenna pair is assumed to overlie a dielectric medium. To assess the performance of the scalar and multicomponent imaging algorithms, we compute their spatial resolution function, which is defined as the image of a point scatterer at a fixed depth using a single frequency. Application of the new multicomponent imaging algorithm results in a circularly symmetric resolution function, demonstrating that the radiation characteristics of the source and receiver antennas do not influence the derived image. In contrast, the two tested scalar imaging algorithms return distinctly asymmetric resolution functions with incorrect phase characteristics, which could result in erroneous images of the subsurface when these algorithms are applied to GPR data. The multicomponent and two scalar imaging algorithms are tested on data acquired across numerous buried objects with various dielectric properties and different strike directions. Phase differences between the different images are similar to those observed in the synthetic examples. Of the tested algorithms, we conclude that the multicomponent approach produces the most reliable results.
A synthetic aperture microwave near-field system is used to image biophysical objects in order to investigate the nature of radar-target interaction. Two different imaging algorithms for focusing data collected over a...
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A synthetic aperture microwave near-field system is used to image biophysical objects in order to investigate the nature of radar-target interaction. Two different imaging algorithms for focusing data collected over a two-dimensional planar aperture are investigated. The first of these is the single frequency backward propagation technique which is mathematically simple to implement and provides a high degree of resolution. Secondly, a multifrequency development of the backward propagation algorithm is presented and derived from two separate perspectives. This latter algorithm, known as the auto-focusing algorithm, requires no information about the range of the target from the aperture. Full characterisation by simulation of both algorithms is carried out and different filtering techniques are investigated. The backward propagation algorithm is applied to the polarimetric imaging of three different leafless trees and a sugar beet plant at the X-band frequency of 10GHz. The images so produced demonstrate that the backscattered signal is dependent on the orientation of individual tree elements with respect to the polarisation. Furthermore, multiple scattering terms can be identified within the structure of the tree. The auto-focusing algorithm is applied to the polarimetric imaging of two trees at 10GHz and repeat measurements are made over several months. As with the single frequency measurements, the backscattered signal is dependent on the orientation of individual tree elements relative to the polarisation. The relative contributions from the leaves and branches of the trees to the backscattered signal are assessed and found to be seasonally dependent. Measurements are also carried out to investigate the variation of backscatter from a beech tree with varying incidence angle. It is demonstrated that at small angles of incidence, the leaves are the dominant source of backscatter but at large incidence angles, the branches and trunk of the tree have the greatest con
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