Abstract:

A recovery and imaging method for missing data of the strip-map mode synthetic aperture radar (SAR) based on compressive sensing (CS) is introduced. The strip-map data is segmented into several sub-apertures,which results in reducing the recovery time significantly. The sub-aperture missing data can be restored by CS and be stitched to the strip-map data. The basis matrix and the measurement matrix for CS are proposed. The sub-aperture data are autofocused by the eigenvector method for maximum-likelihood estimation to meet the sparse requirement of the reconstructed image and the intact phase error data is restored by CS in order to stitch the sub-aperture. A high quality image of the restored data can be obtained by the conventional imaging method and autofocus which corrects the range migration.