Wavefront Reconstruction of Elevation Circular Synthetic Aperture Radar Imagery Using a Cylindrical Green's Function
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Research Article Wavefront Reconstruction of Elevation Circular Synthetic Aperture Radar Imagery Using a Cylindrical Green’s Function Daniel Flores-Tapia,1 Gabriel Thomas,2 and Stephen Pistorius1, 3, 4 1 Division
of Medical Physics, CancerCare Manitoba, Winnipeg, MB, Canada R3E 0V9 of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada R3T 5V6 3 Department of Radiology, University of Manitoba, Winnipeg, MB, Canada R3E 3P5 4 Department of Physics and Astronomy, University of Manitoba, Winnipeg, MB, Canada R3T 2N2 2 Department
Correspondence should be addressed to Daniel Flores-Tapia, [email protected] Received 1 June 2009; Accepted 30 October 2009 Academic Editor: Laurent Ferro-Famil Copyright © 2010 Daniel Flores-Tapia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Elevation Circular Synthetic Aperture Radar (E-CSAR) is a novel radar modality used to form radar images from data sets acquired along a complete or even a segment of a cylindrical geometry above a given scan area. Due to the nonlinear nature of the target signatures on the E-CSAR data sets, the collected data must be focused. In this paper, a novel E-CSAR reconstruction algorithm is proposed. The proposed method uses a new formulation of the Green’s function of an E-CSAR scan geometry in which the phase components introduced by the scan geometry can be clearly identified and their effects can be effectively compensated. Additionally, theoretical aspects of the point spread function related to this new Green’s function were determined. The feasibility of the proposed technique was assessed using experimental data sets. The proposed method yielded spatially accurate images and exhibited an average execution time in the order of minutes.
1. Introduction and Motivation Since its origins in 1951, Synthetic Aperture Radar (SAR) has been used for a wide variety of applications, from military reconnaissance to agricultural imaging to only name two examples [1]. Similarly to other radar imaging modalities, SAR techniques collect the reflections from an irradiated area and process them to create a reflectivity map from the scattering bodies present in the imaged region [2]. The SAR data acquisition process can be described as follows. A trajectory over the scan region is defined. Along this trajectory, an illuminating source radiates an ultra-wideband waveform and records the collected reflections from the objects inside the scan area. The recorded reflections are then processed to eliminate the distortions caused by the antenna, the shape of the irradiated waveform, and the motion of the moving platform [3–5]. Finally, the resulting reflectivity map can be visualized and interpreted. The most commonly used scan geometries in SAR imaging scenarios are linear trajectories [3]. However, this
kind of scan geometries only offer a limited view of the targets p
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