An autofocusing technique of SAR data based on superresolution

Spectral estimation techniques (superresolution) have been studied and implemented in a number of different fields of signal processing for many years. Investigating the feasibility of these techniques on ERS-1 SAR images, the authors have observed that, using superresolution, image focusing is more sensitive to Doppler rate and Doppler centroid than using a conventional approach. In fact, it is well known that in radar imaging the sensitivity of focus respect to system parameters increases with improved resolution, which is the main feature of such non-conventional techniques. The authors propose an autofocusing technique based on the application of superresolution algorithms on a single point target. The technique utilises the image contrast as a quality parameter to compare the sensitivity with respect to conventional map drift and maximum contrast methods. The complete autofocus technique, has been tested with recorded live ERS-1 SAR data. A sensitivity analysis of the application of different spectral estimation algorithms with respect to the common FFT is also provided