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14 October 1998 Comparison of superresolution algorithms
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Abstract
Resolution is a fundamental limitation of any processing based on radar data. Conventional radar imaging techniques, in general, make use of the FFT to determine the spatial location of a target from its scattered field. The resolution of these images is limited by the bandwidth of the interrogating radar system and the aspect angle sector over which the target is observed. In such cases, superresolution offers the potential to improve system performance by increasing the resolution. Superresolution is the process of increasing the effective bandwidth of an image (or time series) by introducing collateral data to augment the dataset; thus the Rayleigh resolution imposed by the size of the dataset is overcome by the introduction of the synthetic collateral data. This paper presents a state of the art survey of radar superresolution, applicable to both 1-D and 2-D data and a comparison of superresolution algorithms using real and simulated data sets. Complex data sets are chosen so as to mimic scenes with a large number of scattering mechanisms. The paper also presents specific applications of superresolution for air-to-ground surveillance, data resolution enhancement, SAR ATR and FOPEN ATR.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Raman K. Mehra, Avinash Gandhe, Melvyn Huff, and Ravi B. Ravichandran "Comparison of superresolution algorithms", Proc. SPIE 3462, Radar Processing, Technology, and Applications III, (14 October 1998); https://doi.org/10.1117/12.326760
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