2-DIMENSIONAL SUPERRESOLUTION SPECTRAL-ANALYSIS APPLIED TO SAR IMAGES

The authors describe the application of modern spectral analysis techn iques to synthetic aperture radar data. The purpose is to improve the geometrical resolution of the image with respect to the numerical valu es related to the compressed coded waveform and the synthetic aperture , so that subsequent classification procedures will have improved perf ormance as well. The classical spectral estimator, i.e. the FFT, produ ces an image with resolution in azimuth and range bounded by the Rayle igh limits. Super-resolved images are obtained by replacing the FFT wi th parametric spectral estimators such as those built around an autore gressive model of the dechirped signal. The proposed processing scheme is based on a two-dimensional covariance method. The expected improve ment in resolution is discussed together with the results of a simulat ion analysis. The application of the technique to images captured by a n airborne SAR resulted in a resolution gain factor of about two. The paper concludes with a perspective on future research and applications .