SAR imaging using combined CS- and TV-regularisation

Abstract:
SAR images include strong scatterers as well as areas with just small fluctuation of power. Moreover, they are usually non-compressible due to the random complex phase of every pixel. Standard regularisation schemes like Compressed Sensing (CS) can not handle this duality. Therefore, we present in this paper a regularisation method on basis of a combination of CS and Total Variation (TV), dividing the measured data in contributions from strong scatterers, surface scatterers and noise. Consequently, imaging using a reduced number of measurements is possible with less artefacts than in case of using standard SAR algorithms.