Abstract
Most imaging systems are adversely affected by the errors in the observation model. One significant example is encountered in synthetic aperture radar (SAR) imaging. Inexact measurement of the distance between the SAR sensing platform and the scene center or random delays on the transmitted signal result in model errors. These errors appear as phase errors in the SAR data and they cause defocusing of the reconstructed image. Mostly, phase errors vary only in the cross-range direction. However, in many scenarios, it is possible to encounter 2D phase errors, which are both range and cross-range dependent. In this study, a sparsity-driven method for joint SAR imaging and phase error estimation is proposed. This method is able to correct 1D as well as 2D phase errors. Experimental results show the effectiveness of the proposed method.
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