Complex-valued interferometric inverse synthetic aperture radar image compression base on compressed sensing

Abstract

Complex-valued interferometric inverse synthetic aperture radar (InISAR) image compression is discussed in this study. The target scene has its continuity and is compressible. However, because of the random phase of each resolution cell, the frequency spectrum of an ISAR image is wide and the complex-valued image is hard to compress. A complex-valued ISAR image compression approach is proposed. Using two or more antennas and interferometry processing, the random phase of image pixel can be cancelled and the frequency spectrum becomes sparse. Therefore the theory of compressed sensing can be introduced to the process of the complex-valued image compression. Hence, the complex-valued InISAR image compression and reconstruction can be completed. Results on real data are presented to validate the method. In comparison with results of the conventional compression techniques, the proposed method shows the better ability to preserve both the imaging magnitude and interferometric phase.

Keywords

• radar imaging
• synthetic aperture radar
• compressed sensing
• image coding
• interferometry
• image resolution
• complex-valued interferometric inverse synthetic aperture radar image compression
• compressed sensing
• resolution cell
• frequency spectrum
• complex-valued ISAR image compression approach
• interferometry processing
• image pixel random phase
• imaging magnitude
• interferometric phase