压缩感知雷达超分辨率成像

doi:10.3969/j.issn.0255-8297.2014.02.004

Abstract

Abstract: Application of compressed sensing (CS) in inverse synthetic aperture radar is investigated in this paper. The radar transmits sparse probing pulses and dechirped radar echo samples that satisfy the Nyquist sampling theorem are resampled sparsely. Reconstruction is performed to these sparse samples both in range and cross-range directions to recover the whole radar echo signals containing the target characteristics. To obtain high resolution ISAR images, super-resolution processing on both range and cross-range directions is conducted on the reconstructed data. Results of processing on real radar data and simulated data show that the resolution of ISAR image can be enhanced significantly. The proposed algorithm can reduce data size and
time consumption, and is valuable for super-resolution radar image applications.

Key words: compressed sensing (CS), radar image, reconstruction, super-resolution

CLC Number:

TN911

DENG Zhen-miao, YE Lin-mei, FU Mao-zhong, ZHANG Yi-xiong. Radar Super-Resolution Imaging Based on Compressive Sensing[J]. Journal of Applied Sciences, 2014, 32(2): 133-140.

References

[1] Richard Baraniuk, Philippe Steeghs. Compressive radar imaging [C]// Radar Conference IEEE, April 2007, 20(7): 128-133.

[2] 高磊，宿绍莹，陈曾平. 宽带雷达Chirp回波的正交稀疏表示及其在压缩感知中的应用 [J]. 电子与信息学报，2011, 33(11): 2720-2726.

GAO Lei, SU Shaoying, CHEN Zengping. Orthogonal sparse representation for chirp echoes in broadband radar and its application to compressed sensing [J]. Journal of Electronics & Information Technology. 2011, 33(11): 2720-2726. (in Chinese)

[3] Matthew A. HERMAN M A, Thomas STROHMER T. High-resolution radar via compressed sensing [J]. IEEE Transactions On Signal Processing, 2009, 57(6): 2275-2284.

[4] Vishal M. PATEL V M, Glenn R. EASLEY G R, Dennis M. HEALY D M Jr., Rama CHELLAPPA R. Compressed synthetic aperture radar [J]. IEEE Journal Of Selected Topics in Signal Processing, 2010, 4(2): 244-254.

[5] ZHAO Guanghui, WANG Zhengyang, WANG Qi, SHI Guangming, SHEN Fangfang. Robust ISAR imaging based on compressive sensing from noisy measurements [J]. Signal Processing, 2012, 92:120-129.

[6] ONHON N O, CETIN M. A Sparsity-driven approach for jiont SAR imaging and phase error correction [J]. Imaging Processing, April 2012, 21(4):2075-2088.

[7] SOLIMENE R, AHMAD F, SOLDOVIERI F. A novel CS-TSVD strategy to perform data reduction in linear inverse scattering problems [J]. IEEE Geoscience and Remote Sensing Letters, September 2012, 9(5): 881-885.

[8] 刘记红，黎湘，徐少坤，庄钊文. 基于改进正交匹配追踪算法的压缩感知雷达成像方法 [J]. 电子与信息学报，2012, 34(6): 1344-1350.

LIU Jihong, LI xiang, XU Shaokun, ZHUANG Zhaowen. Compressed sensing radar imaging methods Based on modified orthogonal matching pursuit algorithms [J]. Journal of Electronics & Information Technology. 2012, 34(6): 1344-1350. (in Chinese)

[9] 徐建平，皮亦鸣，曹宗杰. 基于贝叶斯压缩感知的合成孔径雷达高分辨成像[J]. 电子与信息学报, 2011, 33(12): 2863-2868.

XU Jianping, PI Yiming, CAO Zongjie. SAR imaging based on bayesian compressive sensing [J]. Journal of Electronics & Information Technology. 2011, 33(12): 2863-2868. (in Chinese)

[10] KHWAJA Ahmed Shaharyar, MA Jian Wei. Applications of Compressed Sensing for SAR Moving-Target Velocity Estimation and Image Compression [J]. IEEE Transactions on Instrumentation and Measurement, 2011, 6(8): 2848-2860.

[11] 徐建平，皮亦鸣. 压缩感知SAR成像中的运动补偿 [J].电子与信息学报, 2012, 34(2):294-299.

XU Jianping, PI Yiming. Motion compensation for compressive sensing SAR imaging [J]. Journal of Electronics & Information Technology, 2012, 34(2): 294-299. (in Chinese)

[12] WANG Hongxian, QUAN Yinghui, XING Mengdao, ZHANG Shouhong. ISAR imaging via sparse probing frequencies [J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(3): 451-455.

[13] 刘天鹏，刘振，魏玺章. 基于压缩感知的脉间捷变频SAR成像研 [J]. 电子学报，2012, 40(6): 1073-1078.

Liu Tianpeng, Liu Zhen, Wei Xizhang. Research on interpulse frequency agility SAR imaging via compressed sensing [J]. Journal of Electronics & Information Technology, 2012, 40(6): 1073-1078. (in Chinese)

[14] Hasan S. MIR H S, Blair D. CARLSON B D. On the definition of radar range resolution for targets of greatly differing RCS [J]. IEEE Transactions on Instrumentation and Measurement, 2012, 61(3): 655-663.

[15] ZHANG Lei, XING Mengdao. Achieving higher resolution ISAR imaging with limited pulses via compressed sampling [J]. IEEE Geosience and Remote Sensing Letters, 2009, 6(3): 567-571.

[16] 王伟伟，廖桂生，朱圣棋. 基于压缩感知的双通道SAR地面运动目标检测方法研究 [J]. 电子与信息学报，2012, 34(3): 587-593.

WANG Weiwei, LIAO Guisheng, ZHU Shengqi. A compressive sensing based SAR GMTI method for dual-channel SAR system [J]. Journal of Electronics & Information Technology. 2012, 34(3): 578-593. (in Chinese)

[17] 王伟伟，廖桂生，吴孙勇，朱圣棋. 基于小波稀疏表示的压缩感知SAR成像算法研究 [J]. 电子与信息学报，2011, 33(6): 1440-1446.

WANG Weiwei, LIAO Guisheng, ZHU Shengqi, ZHU Shengqi. A compressive sensing imaging approach based on wavelet sparse representation [J]. Journal of Electronics & Information Technology, 2011, 33(6): 1440-1446. (in Chinese)

[18] 刘记红，徐少坤，高勋章,黎湘. 基于随机卷积的压缩感知雷达成像 [J]. 系统工程与电子技术，2011, 33(7): 1485-1490.

LIU Jihong, XU Shaokun, GAO Xunzhang, LI Xiang. Compressed sensing radar imaging based on random convolution [J]. Systems Engineering and Electronics, 2011, 33(7): 1485-1490. (in Chinese)

[19] 谢晓春，张云华. 基于压缩感知的二维雷达成像算法[J]. 电子与信息学报，2010, 32(5)：1234-1238.

XIE Xiaochun, ZHANG Yunhua. 2D radar imaging scheme based on compressive sensing technique [J]. Journal of Electronics & Information Technology, 2010, 32(5): 1485-1490. (in Chinese)

[20] 江海，林月冠，张冰尘，洪文. 基于压缩感知的随机噪声成像雷达 [J]. 电子与信息学报，2011,33(3): 672-676.

JIANG Hai, LIN Yueguan, ZHANG Bingchen, HONG Wen. Random noise imaging radar based on compressed sensing [J]. Journal of Electronics & Information Technology, 2011, 33(3): 672-676. (in Chinese)

[21] 余慧敏，方广有. 压缩感知理论在探地雷达三维成像中的应用 [J]. 电子与信息学报，2010,32(1): 12-16.

YU Huimin, FANG Guangyou. Research on compressive sensing based 3D imaging method applied to ground penetrating radar [J]. Journal of Electronics & Information Technology, 2010, 32(1): 12-16. (in Chinese)

[22] 屈乐乐，方广有，杨天虹. 压缩感知理论在频率步进探地雷达偏移成像中的应用 [J]. 电子与信息学报，2011,33(1): 21-26.

QU Lele, FANG Guangyou, YANG Tianhong. The application of compressed sensing to stepped-frequency ground penetrating radar migration imaging [J]. Journal of Electronics & Information Technology, 2011, 33(1): 21-26. (in Chinese)

[23] 卢策吾，刘小军，方广有. 基于感知压缩的探地雷达数据压缩采集 [J]. 电子学报，2011, 39(9): 2204-2206.

LU Cewu, LIU Xiaojun, FANG Guangyou. Compressive sensing for GPR date acquisition [J]. Acta Electronica Sinica, 2011, 39(9): 2204-2206. (in Chinese)

[24] QU Lele, YANG Tianhong. Investigation of air/ground reflection and antenna beam width for compressive sensing SFCW GPR migration imaging [J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(8): 3143-3149.

[25] ZHANG Jindong, ZHU Daiyin, ZHANG Gong. Adaptive compressed sensing radar oriented toward cognitive detection in dynamic sparse target scene [J]. IEEE Transactions on Signal Processing, 2012, 60(4): 1718-1729.

[26] Sidney L. BORISON S L, Stephen B. BOWLING S B, Kevin M. CUOMO K M. Super-resolution methods for wideband radar [J]. The Lincoln Laboratory Journal, 1992, 5(3): 441-461.

[27] CUOMO K M. A bandwidth extrapolation technique for improved range resolution of coherent radar data [R]. Project report CJP-60 Rev. 1, Lincoln Laboratory, 4 Dec. 1992, CTIC #ADA-258462.

[28] CUOMO K M, Jean E. PIOU J E, Joseph T. MAYHAN J T. Ultra-wideband coherent processing [J]. The Lincoln Laboratory Journal, 1997, 10(2): 203-222.

[29] PIOU J E, CUOMO K M, MAYHAN J T. A state-space technique for ultrawide-bandwidth coherent processing [J]. Massachusetts Institute of Technology Lincoln Laboratory, July 1999.

[30] 朱兆达，叶纂如，邬小青. 一种超分辨距离多普勒成像方法 [J]. 电子学报, 1992, 20(7)：1-6.

ZHU Zhaoda, YE Zhenru, WU Xiaoqing. An approach to super resolution range-Doppler imaging [J]. Acta Electronica Sinica, 1992, 20(7): 1-6. (in Chinese)

[31] 王琦，周峰，邢孟道，黄金杰. 雷达成像中稀疏孔径外推新算法 [J]. 电子与信息学报, 2007, 29(11): 2698-2701.

WANG Qi, ZHOU Feng, XING Mengdao, HUANG Jinjie. A new algorithm for sparse aperture extrapolation in radar imaging [J]. Journal of Electronics & Information Technology, 2007, 29(11): 2698-2701. (in Chinese)

[32] Donald R. WEHNER D R. High-resolution radar [M]. Artech House, 1995.

[33] Eichel P H, JAKOWATZ C V Jr. Phase-gradient algorithm as an optimal estimator of the phase derivative [J]. Optics Letters, 1989, 14(20): 1101-1103.

[34] 朱兆达，邱晓晖，余志舜. 用改进的多普勒中心跟踪法进行动ISAR补偿 [J]. 电子学报，1997, 25(3): 65-69.

ZHU Zhaoda, QIU Xiaohui, YU Zhishun. ISAR motion compensation using modified Doppler centroid tracking method [J]. Acta Electronica Sinica, 1997, 25(3): 65-69. (in Chinese)

[35] WANG Ling, ZHU Daiyin, ZHU Zhaoda. Improvements of ROPE in ISAR motion compensation [C]// 1st Asian and Pacific Conference on Synthetic Aperture Radar, 2007. APSAR 2007. 735-738.

[36] MUÑOZ-FERRERAS J M, PÉREZ-MARTÍNEZ F. On the Doppler spreading effect for the range-instantaneous-Doppler technique in inverse synthetic aperture radar imagery [J]. Geoscience and Remote Sensing Letters, IEEE, 2010, 7(1): 180-184.

[37] THAYAPARAN T, BRINKMAN W, LAMPROPOULOS G. Inverse synthetic aperture radar image focusing using fast adaptive joint time–frequency and three-dimensional motion detection on experimental radar data [J]. IET Signal Processing, 2010, 4(4): 382–394.

[38] ZHANG Lei, SHENG Jialian, DUAN Jia, XING Mengdao, QIAO Zhijun, BAO Zheng. Translational motion compensation for ISAR imaging under low SNR by minimum entropy [J]. Journal on Advances in Signal Processing, 2013, 2013: 33.

[39] Marco F. DUARTE M F, Richard G. BARANIUK R G. Spectral compressive sensing [J]. Appl. Comput. Harmon. Anal. (2012), http://dx.doi.org/10.1016/j.acha.2012.08.003.

[40] 王军华，黄知涛，周一宇，王丰华. 压缩感知理论中的广义不相关性准则 [J]. 信号处理，2012, 28(5): 675-679.

WANG Junhua, HUANG Zhitao, ZHOU Yiyu, WANG Fenghua. Generalized incoherence principle in compressed sensing [J]. Signal Processing, 2012, 28(5): 675-679. (in Chinese)

[41] Deanna NEEDELL D. Topics in compressed sensing [D]. California: University of California, 2009.

[42] AKAIKE H. Information theory and an extension of the maximum likelihood principle [C]// Proceedings of 2nd International Symposium on Information Theory, 1973: 267-281.

[43] SCHWARTZ G. Estimating the dimension of a model [J]. The Annals of Statistics, 1978, 6(2): 461-464.

[44] CHEN Liang, WU Jiaji, HUANG Bormin. GPU implementation of orthogonal matching pursuit for compressive sensing [C]// 2011 IEEE 17th International Conference on Parallel and Distributed Systems, 7-9 2011: 1044 -1047.

[45] WU Xifei, XIANG Hui, LU Peng. A GPU accelerated algorithm for compressive sensing based Image super-resolution [C]// 2011 Workshop on Digital Media and Digital Content Management, 15-16 May. 2011: 198- 202.

[46] David S. SMITH D S, John C. GORE J C, Thomas E. YANKEELOV T E, E. Brian WELCH E B. Real-time compressive sensing MRI reconstruction using GPU computing and split bregman methods [J]. International Journal of Biomedical Imaging, 2012: 1-6.

Radar Super-Resolution Imaging Based on Compressive Sensing

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	QI Mengyu, ZHAO Lili, LIU Xin, YAN Zhuangzhi. Three-Dimensional Photoacoustic Image Reconstruction Using Weighted Alternating Direction Method [J]. Journal of Applied Sciences, 2019, 37(3): 336-348.
[2]	LI Guo-rui, TIAN Li, CUI Hao, CHEN Hao-bo. An Autoencoder-Based Data Collection Scheme for Wireless Sensor Networks [J]. Journal of Applied Sciences, 2018, 36(3): 411-419.
[3]	TIAN Jin-peng, LIU Xiao-juan, LIU Yan-ping, XUE Ying, ZHENG Guo-xin. Multi-candidate Set of Generalized Orthogonal Matching Pursuit Algorithm [J]. Journal of Applied Sciences, 2017, 35(2): 233-243.
[4]	LIU Ya-wen, QIN Su-shun. Building Facade Reconstruction on Sparse LiDAR Data Region [J]. Journal of Applied Sciences, 2017, 35(2): 217-225.
[5]	ZHANG Guo. Satellite Video Processing and Applications [J]. Journal of Applied Sciences, 2016, 34(4): 361-370.
[6]	YANG Qiong, ZHANG Yi, TANG Cheng-kai, HE Wei. Anti-jamming Algorithm of Space-Time AdaptiveFiltering for GPS Based on MatrixReconstruction [J]. Journal of Applied Sciences, 2016, 34(4): 380-386.
[7]	SUN Jing-feng, LIU Hui-ying, JI Chao, GUO Hui-juan. High-Resolution Image Based on Exponent Moments [J]. Journal of Applied Sciences, 2016, 34(2): 127-134.
[8]	ZHANG Bin, ZHANG Yao-ming, ZHANG Zhi, QIN Qian-qing, WANG Han. Application of Building Information Extraction Based on High Resolution Optical and SAR Images [J]. Journal of Applied Sciences, 2015, 33(5): 559-567.
[9]	JIA Yong-hong1,2, Lü Zhen1, ZHOU Ming-ting1. Super Resolution Reconstruction of ZY-3 Satellite Images [J]. Journal of Applied Sciences, 2015, 33(3): 309-316.
[10]	FENG Xiang1,2, WAN Wang-gen1,2. Sparse Representation and Reconstruction of Image Based on Compressed Sensing [J]. Journal of Applied Sciences, 2014, 32(5): 447-452.
[11]	JIA Ying-biao, FENG Yan, YUAN Xiao-ling, WEI Jiang. Block Compressed Sensing Sampling and Reconstruction Using Spectral Prediction for Hyperspectral Images [J]. Journal of Applied Sciences, 2014, 32(3): 281-286.
[12]	YE Xin-rong1,2, ZHU Wei-ping1, MENG Qing-min1. Sparse Channel Estimation Based on Compressed Sensing for MIMO-OFDM Systems [J]. Journal of Applied Sciences, 2013, 31(3): 245-251.
[13]	LI Xi1, CHEN Feng-rui2, YU Zhi-feng1,3. Spectral Unmixing of Remote Sensing Images Using Interpolation of Wavelet Coefficients [J]. Journal of Applied Sciences, 2012, 30(6): 613-618.
[14]	SUN Guang-ling, SHEN Zhou-biao. Image Super-Resolution Reconstruction Based on Multi-groups of Coupled Dictionary and Alternative Learning [J]. Journal of Applied Sciences, 2012, 30(6): 642-648.
[15]	WANG Yi1;2, ZOU Ji-wei1, YANG Jun-an1;2, LIU Hui1;2, BAI Jing-lu3. Weighted Neighborhood Reconstruction Algorithm and Its Application to Acoustic Target Recognition [J]. Journal of Applied Sciences, 2011, 29(6): 585-591.