OFDM-ISAR的稀疏优化成像与运动补偿

吴敏; 张磊; 刘松杨; 邢孟道

doi:10.12000/JR16017

OFDM-ISAR的稀疏优化成像与运动补偿

DOI: 10.12000/JR16017

(西安电子科技大学西安 710071)

基金项目:

国家自然科学基金(61301280, 61301293),高等学校博士学科点专项科研基金(20120203130001)

详细信息

作者简介:
吴敏(1988-),女,2011年获西安电子科技大学工学学士学位,同年被免试推荐为本校直博生,现为西安电子科技大学雷达国家重点实验室博士生,已先后发表论文8篇,专利1项。主要研究方向为ISAR成像与运动补偿、全极化雷达成像、OFDM雷达成像等。张磊(1984-),男,2006年毕业于长安大学,获学士学位。同年于西安电子科技大学开始硕博连读学习,2012年获西安电子科技大学工学博士学位,现为西安电子科技大学雷达国家重点实验室副教授,研究方向为SAR/ISAR成像与运动补偿。刘松杨(1987-),男,2011年获西安电子科技大学工学学士学位,现为西安电子科技大学博士生,研究方向为雷达对抗、雷达信号处理、雷达指纹识别、电子干扰新技术理论研究。邢孟道(1975-),男,1997年获得西安电子科技大学学士学位,2000年留校工作,2002年获得西安电子科技大学博士学位,目前为西安电子科技大学教授,博士生导师,研究方向为雷达成像、地面动目标检测、目标识别等。

通讯作者:
吴敏wumin880902@hotmail.com

计量
- 文章访问数: 3377
- HTML全文浏览量: 666
- PDF下载量: 1039
- 被引次数: 0
出版历程
- 收稿日期: 2016-01-22
- 修回日期: 2016-01-31
- 网络出版日期: 2016-02-28

OFDM-ISAR Sparse Optimization Imaging and Motion Compensation

(Xidian University, Xi'an 710071, China)

Funds:

The National Natural Science Foundation of China (61301280, 61301293), Doctoral Program of Higher Research Fund (20120203130001)

摘要

摘要: 正交频分复用(OFDM)技术可用以获得无干扰的高分辨距离雷达成像,该文研究利用OFDM波形实现非合作目标的逆合成孔径雷达(ISAR)成像和运动补偿问题。文中讨论了目标平动对循环前缀(CP)长度的影响,利用了ISAR成像的本质稀疏性同时实现成像重建和相位补偿。实验表明,基于CP的OFDM-ISAR运动补偿算法可有效克服OFDM-ISAR成像的距离干扰和运动误差影响,具有较好的稳健性和精确性。
- 逆合成孔径雷达(ISAR)成像 /
- 正交频分复用(OFDM) /
- 循环前缀(CP) /
- 运动补偿
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) technology has been utilized in radar imaging to obtain high-resolution range profiles without inter-range cell interference. In this study, we establish a novel algorithm for Inverse Synthetic Aperture Radar (ISAR) imaging of a non-cooperative target using OFDM waveforms. We also achieve motion compensation and image enhancement with sparse reconstruction optimization. Utilizing sparse reconstruction optimization, we can simultaneously achieve high-precision OFDM-ISAR imaging and also correct phase errors. Extensive experimentation confirms that the proposed method can effectively overcome range interference and phase errors in OFDM-ISAR imaging, providing optimal robustness and precision.
- Inverse Synthetic Aperture Radar (ISAR) imaging /
- Orthogonal Frequency Division Multiplexing (OFDM) /
- Cyclic Prefix (CP) /
- Motion compensation

HTML全文

参考文献(17)

[1]	Soumekh M. Synthetic Aperture Radar Signal Processing[M]. NewYork, NY, USA: Wiley, 1999.
[2]	Axelsson S R J. Analysis of random step frequency radar and comparison with experiments[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(4): 890-904.
[3]	Riche V, Meric S, Baudais J, et al.. Optimization of OFDM SAR signals for range ambiguity suppression[C]. 2012 9th European Radar Conference (EuRAD), Amsterdam, 2012: 278-281.
[4]	Kim J H, Younis M, Moreira A, et al.. A novel OFDM chirp waveform scheme for use of multiple transmitters in SAR[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(3): 568-572.
[5]	Garmatyuk D and Brenneman M. Adaptivemulticarrier OFDM SAR signal processing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 3780-3790.
[6]	Zhang T and Xia X G. OFDM synthetic aperture radar imaging with sufficient cyclic prefix[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(1): 394-404.
[7]	Zhang T, Xia X G, and Kong L. IRCI free range reconstruction for SAR imaging with arbitrary length OFDM pulse[J]. IEEE Transactions on Signal Processing, 2014, 62(18): 4748-4759.
[8]	Chen C C and Andrews H C. Target-motion-induced radar imaging[J]. IEEE Transactions on Aerospace and Electronic Systems, 1980, 16(1): 2-14.
[9]	Wang J and Kasilingam D. Global range alignment for ISAR[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(1): 351-357.
[10]	Donoho D. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.
[11]	吴敏, 邢孟道, 张磊. 基于压缩感知的二维联合超分辨ISAR成像算法[J]. 电子与信息学报, 2014, 36(1): 187-193. Wu Min, Xing Meng-dao, and Zhang Lei. Two dimensional joint super-resolution ISAR imaging algorithm based on compressive sensing[J]. Journal of Electronics Information Technology, 2014, 36(1): 187-193.
[12]	Du X, Duan C, and Hu W. Sparse representation based autofocusing technique for ISAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(3): 1826-1835.
[13]	Zhao L, Wang L, Bi G, et al.. An autofocus technique for high-resolution inverse synthetic aperture radarimagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(10): 6392-6403.
[14]	Rao W, Li G, Wang X, et al.. Parametric sparse representation method for ISAR imaging of rotating targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 910-919.
[15]	Baraniuk R and Steeghs P. Compressive radar imaging[C]. 2007 IEEE Radar Conference, Boston, MA, 2007: 128-133.
[16]	Duarte M F and Baraniuk R G. Kronecker compressive sensing[J]. IEEE Transactions on Image Processing, 2012, 21(2): 494-504.
[17]	Axelsson O. Iterative Solution Methods[M]. Cambridge, U.K.: Cambridge University Press, 1994.