引用本文: 任笑真, 杨汝良. 一种基于幅度和相位迭代重建的四维合成孔径雷达成像方法[J]. 雷达学报, 2016, 5(1): 65-71. doi: 10.12000/JR15135
Ren Xiaozhen, Yang Ruliang. Four-dimensional SAR Imaging Algorithm Based on Iterative Reconstruction of Magnitude and Phase[J]. Journal of Radars, 2016, 5(1): 65-71. doi: 10.12000/JR15135
 Citation: Ren Xiaozhen, Yang Ruliang. Four-dimensional SAR Imaging Algorithm Based on Iterative Reconstruction of Magnitude and Phase[J]. Journal of Radars, 2016, 5(1): 65-71. doi: 10.12000/JR15135

## Four-dimensional SAR Imaging Algorithm Based on Iterative Reconstruction of Magnitude and Phase

Funds:

The National Natural Science Foundation of China (61201390), The Key Scientific Research Project in Universities of Henan Province (16A510004), The Plan for Young Backbone Teacher of Henan Province (2015GGJS038)

• 摘要: 4维合成孔径雷达获取的观测数据在基线-时间平面非均匀分布。若采用传统成像方法来获取目标散射体的高度-速率维像,则因强副瓣存在,成像效果不理想。当信号具有稀疏性时,压缩感知技术能够利用少量的信号投影值就可实现信号的准确或近似重构。然而标准的压缩感知成像方法是针对实数据进行处理,4维合成孔径雷达成像处理的数据为复数据。因此该文提出了一种基于幅度和相位迭代重建的4维合成孔径雷达成像方法。将4维合成孔径雷达高度-速率成像问题转化为目标复散射系数的幅度和相位联合重建问题,通过在成像过程中引入相位信息来改善成像质量。仿真结果验证了该算法的有效性。

•  [1] Morrison K, Bennett J C, and Nolan M. Using DInSAR to separate surface and subsurface features[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(6): 3424-3430. [2] Fornaro G, D'Agostino N, Giuliani R, et al.. Assimilation of GPS-derived atmospheric propagation delay in DInSAR data processing[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(2): 784-799. [3] Fornaro G, Reale D, and Serafino F. Four-dimensional SAR imaging for height estimation and monitoring of signal and double scatterers[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(1): 224-237. [4] Lombardini F. Differential tomography: a new framework for SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(1): 37-44. [5] Reigber A, Lombardini F, Viviani F, et al.. Three-dimensional and higher-order imaging with tomographic SAR: techniques, applications, issues[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 2015: 2915-2918. [6] Serafino F, Soldovieri F, Lombardini F, et al.. Singular value decomposition applied to 4D SAR imaging[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Seoul, Korea, 2005: 2701-2704. [7] 孙希龙, 余安喜, 董臻, 等. 一种差分SAR层析高分辨成像方法[J]. 电子与信息学报, 2012, 34(2): 273-278. Sun Xi-long, Yu An-xi, Dong Zhen, et al.. A high resolution method for differential SAR tomography[J]. Journal of Electronics Information Technology, 2012, 34(2): 273-278. [8] 任笑真, 杨汝良. 一种基于逆问题的差分干涉SAR层析成像方法[J]. 电子与信息学报, 2010, 32(3): 582-586. Ren Xiao-zhen and Yang Ru-liang. An inverse problem based approach for differential SAR tomography imaging[J]. Journal of Electronics Information Technology, 2010, 32(3): 582-586. [9] Candes E J, Romberg J, and Tao T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information[J]. IEEE Transactions on Information Theory, 2006, 52(2): 489-509. [10] Donoho D. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306. [11] Zhu X X and Bamler R. Sparse reconstruction techniques for SAR tomography[C]. 17th International Coference on Digital Signal Processing, Corfu, Greece, 2011: 1-8. [12] Ren Xiao-zhen and Chen Li-na. Four-dimensional SAR imaging algorithm using Bayesian compressive sensing[J]. Journal of Electromagnetic Waves and Applications, 2014, 28(13): 1661-1676. [13] Cetin M and Karl W C. Feature enhanced synthetic aperture radar image formation based on non-quadratic regularization[J]. IEEE Transactions on Image Processing, 2001, 10(4): 623-631. [14] Samadi S, Cetin M, and Masnadi-Shirazi M A. Sparse representation-based synthetic aperture radar imaging[J]. IET Radar, Sonar Navigation, 2011, 5(2): 182-193.

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##### 出版历程
• 收稿日期:  2015-12-31
• 修回日期:  2016-01-24

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