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Modern spectral estimation techniques (superresolution in technical jargon) have been applied to many fields of signal processing since many years[l], . Application to radar imaging, mainly to ISAR (Inverse Synthetic Aperture Radar) is documented in some recent papers to . Appiications have been attempted also to SAR (Synthetic Aperture Radar), . In these fields the benefit of spectral estimation reveals in a resolution beyond the Rayleigh limits set by compressed pulse and synthetic aperture lengths. Furthermore very low sidelobes of point scatterer response are obtained. In this paper superresolution has been applied both to stepped-frequency ISAR data and to real ERS-1 SAR data; the achieved results are encouraging and suggest a more extensive practical application of the technique. The paper is organised in two parts. In the first we have applied the autoregressive (AR) and the minimum variance (MV)-Capon methods to improve the range resolution of simulated ISAR data. In the second part we have conceived an upgraded version of spectral analysis (SPECAN) processing to obtain a SAR image of better quality. The method has been tested on recorded live data of ERS-1 mission.