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DLSLA 3-D SAR imaging algorithm for off-grid targets based on pseudo-polar formatting and atomic norm minimization

Science China(Information Sciences) 2016年第6期59卷 225-239页

作者： Qian BAO Kuoye HAN Xueming PENG Wen HONG Bingchen ZHANG Weixian TAN Science and Technology on Microwave Imaging Laboratory (MITL) Institute of ElectronicsChinese Academy of Sciences (IECAS) School of Electronic and Communication Engineering University of Chinese Academy of Sciences (UCAS) Information System Technology Institute Information Science Academy of China Electronics Technology Group Corporation Global RD Centre (Shanghai) Carestream Health Incorporated College of Information Engineering Inner Mongolia University of Technology

This paper concerns the imaging problem for downward looking sparse linear array three-dimensional synthetic aperture radar(DLSLA 3-D SAR) under the circumstance of sparse and non-uniform cross-track dimensional virtual phase centers configuration. Since the 3-D imaging scene behaves typical sparsity in a certain domain, sparse recovery approaches hold the potential to achieve a better reconstruction performance. However,most of the existing compressive sensing(CS) algorithms assume the scatterers located on the pre-discretized grids, which is often violated by the off-grid effect. By contrast, atomic norm minimization(ANM) deals with sparse recovery problem directly on continuous space instead of discrete grids. This paper firstly analyzes the off-grid effect in DLSLA 3-D SAR sparse image reconstruction, and then introduces an imaging method applied to off-gird targets reconstruction which combines 3-D pseudo-polar formatting algorithm(pseudo-PFA) with ANM. With the proposed method, wave propagation and along-track image reconstruction are operated with pseudo-PFA, then the cross-track reconstruction is implemented with semidefinite programming(SDP) based on the ANM model. The proposed method holds the advantage of avoiding the off-grid effect and managing to locate the off-grid targets to accurate locations in different imaging scenes. The performance of the proposed method is verified and evaluated by the 3-D image reconstruction of different scenes, i.e., point targets and distributed scene.

关键词： atomic norm minimization DLSLA 3-D SAR sparse recovery off-grid targets pseudo-PFA 3-D imaging

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