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SAR Image Reconstruction from 1-Bit Quantized Data with Sign-Flip Errors

Compressed Sensing (CS) theory emerged in recent years provide important benefits in Synthetic Aperture Radar (SAR) Imaging. Recent studies have shown that CS also provides good results in obtaining SAR images from 1-bit quantized measurements. However, in 1-bit SAR imaging, while signals are being transmitted or acquired, sign-flip errors occur due to noise in the measurements. In this study, a new SAR image recovery approach is formed by integrating adaptive outlier pursuit (AOP) method into fast iterative shrinkage thresholding algorithm (FISTA) to reduce SAR image deterioration caused by sign-flip errors.