Phase adjustment for polarimetric ISAR with compressive sensing

Polarimetric inverse synthetic aperture radar (pol-ISAR) imaging exploits extra scattering information about a target compared with single pol-ISAR. Target description and classification can be improved by incorporating pol-ISAR images. One of the most critical problems in ISAR imaging is accurate motion compensation, specifically for noncooperative targets. Due to the imperfection of coarse motion compensation, phase-adjustment methods are further developed to eliminate the residual phase errors. Unlike taking the contrast or entropy as the measurements in the existing pol-ISAR phase-adjustment algorithms, this paper exploits the sparsity of the scattering centers to correct the phase errors and simultaneously proposes an unambiguous image formation with the sparse aperture signal. The superiority of this algorithm is that the global information of full pol-ISAR images can be properly incorporated to compensate the phase errors and suppress the noise effectively. Experimental results indicate the effectiveness of the proposed method.