Conventional matched filtering based algorithms are not sufficiently good at dealing with the anisotropic backscattering behavior of targets in Wide Angle SAR (WASAR) imaging. Sparse signal processing provides a new idea for this problem, the anisotropic problem is modeled as a group of under-determined linear equations. However, the scale of unknowns in the under-determined equations is in linear order of the number of the observation angle. As the observation angle increases, the anisotropic problem becomes more and more difficult to be solved, even failed for conventional sparse signal processing algorithms. This paper presents a Group- sparse Complex Approximated Message Passing (GCAMP) algorithm for WASAR imaging. Firstly, a group sparse based WASAR imaging model is provided according to the structured property of backscattering coefficients across different observation angles. Secondly, the GCAMP algorithm is derived from the imaging model using message passing theory. Results of simulation demonstrate the effectiveness of the proposed algorithm.%传统相关处理算法不能完全解决宽角合成孔径雷达(WASAR)成像中目标的散射特性随观测角度变化的问题。稀疏信号处理为该问题提供一种新思路，各向异性问题可以建模成欠定方程组。随角度增大，未知量的规模以观测孔径数目的线性规模增长，导致成功重建难度增大，甚至是重建失败。该文提出一种基于信息传递原理的宽角合成孔径雷达成像方法。根据宽角合成孔径雷达的观测几何及目标散射特性在不同角度之间存在的相关性，建立基于结构稀疏的成像模型；然后利用信息传递原理，提出基于结构稀疏复数信息传递(GCAMP)的成像算法求解该成像模型。仿真结果验证了该方法的有效性。
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