| Citation: | XIONG Shichao, NI Jiacheng, ZHANG Qun, et al. 2-D compressed sensing SAR imaging based on mixed sparse representation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(11): 2314-2324. doi: 10.13700/j.bh.1001-5965.2021.0101(in Chinese)
|
Compressed sensing (CS) theory has been applied in synthetic aperture radar (SAR) in the recent years. A 2-D CS SAR imaging method is proposed using mixed sparse representation (MSR) based on approximate observation model in non-sparse scene compressed sensing SAR imaging. Firstly, non-sparse scene with complicated ground features is decomposed into point-like, edges and smooth components. Then, edges and smooth components are transformed into sparse domain by discrete cosine transform and curvelet transform respectively. And based on approximate observation model, SAR images are derived from 2-D CS optimization problem. Owing to the sparse representation method of non-sparse scene, the proposed method can realize high quality SAR imaging for non-sparse scene. Compared to the existing method, the proposed method has better reconstruction quality for region containing distinct edges and lines, such as city and river. Both the simulation scene and real scene experiments demonstrate the effectiveness of the proposed method.
| [1] |
吴一戎, 洪文, 张冰尘, 等. 稀疏微波成像研究进展[J]. 雷达学报, 2014, 3(4): 383-395. https://www.cnki.com.cn/Article/CJFDTOTAL-LDAX201404002.htm
WU Y R, HONG W, ZHANG B C, et al. Current developments of sparse microwave imaging[J]. Journal of Radars, 2014, 3(4): 383-395(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-LDAX201404002.htm
|
| [2] |
倪嘉成, 张群, 顾福飞, 等. 基于马尔科夫链的单站SAR海面场景宽幅高分成像算法[J]. 航空学报, 2016, 37(12): 3793-3802. https://www.cnki.com.cn/Article/CJFDTOTAL-HKXB201612024.htm
NI J C, ZHANG Q, GU F F, et al. Mono-static SAR HRWS imaging algorithm of sea surface based Markov chain[J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(12): 3793-3802(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HKXB201612024.htm
|
| [3] |
DONOHO D. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306. doi: 10.1109/TIT.2006.871582
|
| [4] |
CANDES E J, WAKIN M B. An introduction to compressive sampling[J]. IEEE Signal Processing Magazine, 2008, 25(2): 21-30. doi: 10.1109/MSP.2007.914731
|
| [5] |
SAMADI S, CETIN M, MASNADI-SHIRAZI M A. Sparse representation-based synthetic aperture radar imaging[J]. IET Radar Sonar and Navigation, 2009, 5(2): 182-193.
|
| [6] |
FANG J, XU Z B, ZHANG B C, et al. Fast compressed sensing SAR imaging based on approximated observation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(1): 352-363. doi: 10.1109/JSTARS.2013.2263309
|
| [7] |
顾福飞, 张群, 杨秋, 等. 基于NCS算子的大斜视SAR压缩感知成像方法[J]. 雷达学报, 2016, 5(1): 16-24. https://www.cnki.com.cn/Article/CJFDTOTAL-LDAX201601004.htm
GU F F, ZHANG Q, YANG Q, et al. Compressed sensing imaging algorithm for high-squint SAR based on NCS operator[J]. Journal of Radars, 2016, 5(1): 16-24(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-LDAX201601004.htm
|
| [8] |
BI H, BI G A, ZHANG B C, et al. From theory to application: Realtime sparse SAR imaging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(4): 2928-2936. doi: 10.1109/TGRS.2019.2958067
|
| [9] |
SHKVARKO Y V, Y ANEZ J I, AMAO J A. Radar/SAR image resolution enhancement via unifying descriptive experiment design regularization and wavelet-domain processing[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(2): 152-156. doi: 10.1109/LGRS.2015.2502539
|
| [10] |
ZHANG C L, LIU Y L, WAN F Y, et al. Multi-faults diagnosis of rolling bearings via adaptive customization of flexible analytical wavelet bases[J]. Chinese Journal of Aeronautics, 2020, 33(2): 407-417. doi: 10.1016/j.cja.2019.03.014
|
| [11] |
彭才, 常智, 朱仕军. 基于曲波变换的地震数据去噪方法[J]. 石油勘探, 2008, 47(5): 461-464. https://www.cnki.com.cn/Article/CJFDTOTAL-SYWT200805008.htm
PENG C, CHANG Z, ZHU S J. Noise elimination method based on curvelet trans-form[J]. Geophysical Prospecting for Petroleum, 2008, 47(5): 461-464(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SYWT200805008.htm
|
| [12] |
CETIN M, STOJANOVIC I, ONHON O, et al. Sparsity-driven synthetic aperture radar imaging: Reconstruction, autofocusing, moving targets and compressed sensing[J]. IEEE Signal Processing Magazine, 2014, 31(4): 27-40. doi: 10.1109/MSP.2014.2312834
|
| [13] |
SADEGH S, MUJDAT C, MOHAMMAD A M. Multiple feature enhanced SAR imaging using sparsity in combined dictionaries[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(4): 821-825. doi: 10.1109/LGRS.2012.2225016
|
| [14] |
SHEN F F, ZHAO G H, LIU Z C, et al. SAR imaging with structural sparse representation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(8): 3902-3910. doi: 10.1109/JSTARS.2014.2364294
|
| [15] |
MICHAL A, MICHAEL E, ALFRED B. K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Transactions on Signal Processing, 2006, 54(11): 4311-4322. doi: 10.1109/TSP.2006.881199
|
| [16] |
胡长雨, 汪玲, 朱栋强. 结合字典学习技术的ISAR稀疏成像方法[J]. 电子与信息学报, 2019, 41(7): 1735-1742. https://www.cnki.com.cn/Article/CJFDTOTAL-DZYX201907028.htm
HU C Y, WANG L, ZHU D Q. Sparse ISAR imaging exploiting dictionary learning[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1735-1742(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-DZYX201907028.htm
|
| [17] |
LI F, XIN L, GUO Y, et al. A framework of mixed sparse representations for remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(2): 1210-1221.
|
| [18] |
LI B, LIU F L, ZHOU C B, et al. Mixed sparse representation for approximated observation-based compressed sensing radar imaging[J]. Journal of Applied Remote Sensing, 2018, 12(3): 1-21.
|
| [19] |
DABECHIES I, DEFRISE M, DEMOL C. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint[J]. Communications on Pure and Applied Mathmatics, 2004, 57(11): 1413-1457.
|
| [20] |
RANEY R K, RUNGE H, BAMLER R, et al. Precision SAR processing using chirp scaling[J]. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(4): 786-799.
|
| [21] |
CANDES E, DEMANET L, DONOHO D. Fast discrete curvelet transforms[J]. Multiscale Modeling & Simulation, 2006, 5(3): 861-899.
|
Figures(11) / Tables(2)
Copyright © Journal of Beijing University of Aeronautics and Astronautics
Address: Editorial Department of Journal of Beijing University of Aeronautics and Astronautics, 37 Xueyuan Road, Haidian District, Beijing Post Code: 100191 Email: jbuaa@buaa.edu.cn
Supported by:
Beijing Renhe Information Technology Co., Ltd.
DownLoad:
