Autofocus algorithm using blind homomorphic deconvolution for synthetic aperture radar imaging. Issue 7 (1st August 2015)

• Record Type: Journal Article
• Authors: Shao, Peng; Xing, Mengdao; Xia, Xiang‐Gen; Li, Yachao; Li, Xueshi; Bao, Zheng
• Is Part Of: IET radar, sonar & navigation. Volume 9:Issue 7(2015)
• Page Start: 900
• Page End: 906
• Publication Date: 2015-08-01
• Subjects: synthetic aperture radar -- radar imaging -- deconvolution -- airborne radar -- phase estimation -- iterative methods -- wavelet transforms -- image reconstruction -- computational complexity; autofocus algorithm -- blind homomorphic deconvolution -- synthetic aperture radar imaging -- unknown phase error -- atmosphere perturbation -- wavelet scaling function -- iterative estimation -- computational complexity -- data processing; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2014.0399
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : In airborne case, synthetic aperture radar images generally suffer from the deterioration because of the unknown phase error caused by unstable platform and atmosphere perturbation. To obtain the phase error, a novel autofocus algorithm referred to as blind homomorphic deconvolution autofocus algorithm is proposed in this study. In this method, a wavelet scaling function is used to construct a smooth subspace that is orthogonal to noise subspace. Then, the phase error can be separated and reconstructed by the generated smooth subspace based on the differences of the smoothness properties between phase error and image reflectivity. Compared with the traditional autofocus methods, the proposed method does not require an iterative estimation. Thus, the computational complexity can be significantly reduced. Simulation and real data processing results validate the effectiveness of the proposed method.