Two-dimensional super-resolution spectral analysis applied to SAR images

The authors describe the application of modern spectral analysis techniques to synthetic aperture radar data. The purpose is to improve the geometrical resolution of the image with respect to the numerical values related to the compressed coded waveform and the synthetic aperture, so that subsequent classification procedures will have improved performance as the classical spectral estimator, i.e., the FFT, produces an image with resolution in azimuth and range bounded by the Rayleigh limits. Super-resolved images are obtained by replacing the FFT with parametric spectral estimators such as those built around an autoregressive model of the dechirped signal. The proposed processing scheme is based on a two-dimensional covariance method. The expected improvement in resolution is discussed together with the results of a simulation analysis. The application of the technique to images captured by an airborne SAR resulted in a resolution gain factor of about two. The paper concludes with a perspective on future research and applications