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9 June 1994 Application of one-dimensional adaptive extrapolation to improve resolution in range-Doppler imaging
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A recent 1D, nonparametric procedure to extrapolate a signal is evaluated for resolution enhancement in inverse SAR imaging. This algorithm, denoted adaptive weighted norm extrapolation (AWNE), is based on iterative use of minimum weighted norm extrapolation to provide a stationary extension of the given data. Computing the discrete Fourier transform (DFT) spectrum of this signal completes the last step of this procedure when used as a spectrum estimator. In this paper the AWNE procedure is used in two directions to obtain range-Doppler images with improved resolution. We evaluate the results and compare them with those obtained with the conventional method based on the DFT. Using rectangularly sampled target data of noise corrupted point scatterers, we show that the AWNE approach produces accurate component locations and amplitudes as well as the expected higher resolution. Our examples show results for arrays of 63 by 63 samples extrapolated to 128 by 128 and 256 by 256. Next, we illustrate the application of AWNE to point scatterer data taken on a polar raster after it has undergone polar reformatting. The procedure is insensitive to the finite accuracy of the reformatting procedure needed to fit the samples into a rectangular raster. Finally, we illustrate the use of AWNE on an array of 64 by 64 data points to form the image of a Boeing 727 aircraft and compare results with those obtained via the conventional DFT processing.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sergio D. Cabrera, Benjamin C. Flores, Gabriel Thomas, and Javier Vega-Pineda "Application of one-dimensional adaptive extrapolation to improve resolution in range-Doppler imaging", Proc. SPIE 2230, Algorithms for Synthetic Aperture Radar Imagery, (9 June 1994);


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