Tomographic 3D reconstruction from airborne circular SAR
ABSTRACT The study of data acquired over a circular trajectory has raised an increasing interest in the SAR community. Two main reasons summarize the interest in such geometry. First, sub-wavelength resolution can be achieved, as the targets in the spotted area are observed under a 360o aperture. Second, the use of the information from different azimuthal directions allows one to obtain information of the scene in the third dimension, making possible a 3D target reconstruction. In any case, both applications require certain target reflectivity homogeneity. This paper shows several processing results and analyzes the potentials and limitations of circular SAR to perform tomography of semi-transparent media. Special processing aspects, like the estimation of residual motion errors due to inaccuracies in the navigation data, are also addressed. Data acquired at L-band by DLR's E-SAR system are used to demonstrate the high resolution and tomographic imaging capabilities of circular SAR. The results include the tomogram of a Luneburg lens, as well as preliminary results over man-made targets and vegetation.
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ABSTRACT: This article presents a modified Omega-K algorithm for circular trajectory scanning synthetic aperture radar (CTSSAR) imaging. Due to the curvature of circular trajectory, it is difficult to have access to the two-dimensional frequency spectrum for CTSSAR via the principle of stationary phase (POSP), as conventional SAR imaging methods RD and CS. Herein, the analytic point target spectrum is first derived by series reversion and the POSP, based on which a modified Omega-K algorithm is developed to focus data accurately. The accuracy can be controlled by keeping enough terms in the two series expansions so that a well-focused image can be achieved with a proper range approximation. After detailed analyses and experiments, the fourth-order approximation is proved to be the best choice. Furthermore, the computational efficiency is evaluated by comparing the given method with the back projection algorithm and other methods with different approximated orders. The proposed algorithm is verified to be the best one in terms of computational burden. A well-focused image is obtained by simulations, validating the feasibility of the proposed algorithm.Journal on Advances in Signal Processing 01/2013; 2013(1). DOI:10.1186/1687-6180-2013-64 · 0.81 Impact Factor
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ABSTRACT: This paper describes the implementation of an efficient implementation of a Fast Factorized Back Projection (FFBP) algorithm for Circular SAR (CSAR) trajectories for real airborne data. Unlike Fourier-domain based focusing processors, this approach considers the azimuth variance and topography changes with high accuracy, while improving significantly the computational time factor in comparison with the direct Back Projection (BP). To further accelerate the focusing, the circular FFBP was implemented also on a Graphics Processor Unit (GPU). In the second part of the document is shown a fully polarimetric image of the region of Kaufbeuren, Germany, (acquired by the DLR’s E-SAR system) focused with this method to the theoretical limit of lambda over four. Thus, the efficiency, accuracy and performance of the circular FFBP is demonstrated, as well as the potential of CSAR when focusing over 360 ◦.IEEE International Geoscience and Remote Sensing Symposium (IGARSS); 01/2011
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ABSTRACT: This letter presents a new algorithm for squint circular synthetic aperture radar (SAR) (CSAR) imaging, which is an extension of the well-known range migration algorithm. Due to the circular trajectory, the spatial frequency domain data of squint CSAR cannot be readily obtained via fast Fourier transform, as conventional SAR with straight path does. This method first employs along-track varying system kernels and filters to transform the raw data to the polar spatial frequency domain. Then, it uses an interpolation algorithm to convert the polar samples into rectilinear samples. Implementation aspects, including sampling criteria, resolutions, and computational complexity, are also assessed in this letter. The proposed algorithm is validated both numerically and experimentally.IEEE Geoscience and Remote Sensing Letters 08/2011; 8(4-8):651 - 655. DOI:10.1109/LGRS.2010.2098843 · 1.81 Impact Factor