Phase Error Compensation in Imaging Systems Using Compressed Sensing Techniques

A study of the capabilities for phase error correction of compressed sensing (CS) imaging techniques is presented. The idea is to show that CS method is able to recover reflectivity images with a reduced number of sensors even if the system suffers from phase errors. A comparison to the sparsity-driven approach (SDA) technique for phase error correction is presented, analyzing SDA and CS performance with different numbers of sensors, phase error values, and sensor placement uncertainties. Validation with synthetically blurred experimental data-collected using multistatic radar-is presented.

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