一种基于压缩感知恢复算法的SAR图像方位模糊抑制方法

肖鹏; 吴有明; 于泽; 李春升

doi:10.12000/JR16004

一种基于压缩感知恢复算法的SAR图像方位模糊抑制方法

DOI: 10.12000/JR16004

(北京航空航天大学电子信息工程学院北京 100191)

基金项目:

国家重点基础研究发展计划973计划(2010CB731902)

详细信息

作者简介:
肖鹏(1984-),男,黑龙江哈尔滨人,2014年获得北京航空航天大学工学博士学位,现为北京航空航天大学博士后,主要研究方向为雷达信号处理新方法及星载SAR系统新体制设计。E-mail:xiaopeng_email1984@163.com吴有明(1990-),男,江西南昌人,北京航空航天大学电子信息工程学院在读博士生,主要研究方向为合成孔径雷达信号处理、稀疏微波成像。E-mail:youmingwu@buaa.edu.cn于泽(1979-),男,博士,副教授,现任职于北京航空航天大学电子信息工程学院。分别于2002年、2007年在北京航空航天大学获得学士学位和博士学位。目前主要研究方向包括天基雷达系统体制设计、高分辨SAR成像处理、稀疏目标特征重建等。E-mail:yz613@buaa.edu.cn

通讯作者:
肖鹏xiaopeng_email1984@163.com

计量
- 文章访问数: 3114
- HTML全文浏览量: 519
- PDF下载量: 1182
- 被引次数: 10
出版历程
- 收稿日期: 2016-01-05
- 修回日期: 2016-01-25
- 网络出版日期: 2016-02-28

Azimuth Ambiguity Suppression in SAR Images Based on Compressive Sensing Recovery Algorithm

(School of Electronic and Information Engineering, Beihang University, Beijing 100191, China)

Funds:

National Key Basic Research Program Project (973 Program) of China (2010CB731902)

摘要

摘要: 方位模糊现象广泛存在于星载合成孔径雷达图像中。当模糊能量较强时,会出现大量的虚假目标,严重影响对图像的判读。由于模糊能量与真实主区能量在时域、频域中均互相混叠,现有的处理方法很难在不损失分辨率的条件下,有效抑制方位模糊所产生的鬼影。该文提出一种基于压缩感知恢复算法的方位模糊抑制方法,通过截断图像的多普勒频谱实现模糊抑制,而后将原始图像作为先验信息、将截断谱作为观测结果,利用压缩感知恢复算法,迭代求解出高分辨率的图像。经过仿真与真实数据验证,该方法可以有效抑制方位模糊能量,而不损失主区目标分辨能力,且对复杂场景同样具有良好的效果。
- 星载SAR /
- 方位模糊抑制 /
- 压缩感知
Abstract: Azimuth ambiguities appear widely throughout spaceborne Synthetic Aperture Radar (SAR) images. If the ambiguous energy is relatively strong, a large number of brilliant areas or points will emerge, which may be erroneously judged as actual targets. This is a disadvantage in image interpretation. Due to the fact that ambiguous energy is mixed with energy from the main zone in the frequency and time domains, it is difficult to suppress azimuth ambiguity to a reasonable level using the existing approach without loss of resolution. This study proposes an innovative approach for suppressing azimuth ambiguity based on the compressive sensing recovery framework, in which the original image acts as prior information and the corresponding frequency spectrum truncated in a proper ratio acts as measurement information. With the proposed approach, highresolution low-ambiguity images can be obtained by iteration. We used simulation and satellite data to validate the effectiveness of this proposed approach in suppressing azimuth ambiguity.
- Spaceborne SAR /
- Azimuth ambiguity suppression /
- Compressive Sensing (CS)

HTML全文

参考文献(14)

[1]	Curlander J C and Mcdonough R N著. 韩传钊, 等译. 合成孔径雷达: 系统与信号处理[M]. 北京: 电子工业出版社, 2006: 205-214. Curlander J C, Mcdonough R N, Han C Z, et al.. Synthetic Aperture Radar: Systems and Signal Processing[M]. Beijing: Electronic Industry Press, 2006: 205-214.
[2]	Runge H, Laux C, Gabele M, et al.. Performance analysis of virtual multi-channel modes for TerraSAR-X[C]. EUSAR, 2006: 1-4.
[3]	Moreira A. Suppressing the azimuth ambiguities in synthetic aperture radar images[J]. IEEE Transactions on Geoscience and Remote Sensing, 1993, 31(4): 885-895.
[4]	Wang K, Chen J, Yang W, et al.. Suppression of azimuth ambiguities in spaceborne stripmap SAR using accurate restoration modeling[C]. 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2015), Milan, Italy, 2015: 2429-2432.
[5]	Guarnieri A M. Adaptive removal of azimuth ambiguities in SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(3): 625-633.
[6]	Donoho D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.
[7]	Cand E J and Wakin M B. An introduction to compressive sampling[J]. IEEE Signal Processing Magazine, 2008, 25(2): 21-30.
[8]	Di Martino G, Iodice A, Riccio D, et al.. Filtering of azimuth ambiguity in stripmap synthetic aperture radar images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(9): 3967-3978.
[9]	Chen J, Iqbal M, Yang W, et al.. Mitigation of azimuth ambiguities in spaceborne stripmap SAR images using selective restoration[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(7): 4038-4045.
[10]	吴一戎, 洪文, 张冰尘, 等. 稀疏微波成像研究进展(科普类)[J]. 雷达学报, 2014, 3(4): 383-395. Wu Yirong, Hong Wen, Zhang Bingchen, et al.. Current developments of sparse microwave imaging[J]. Journal of Radars, 2014, 3(4): 383-395.
[11]	Zhang B C, Hong W, and Wu Y R. Sparse microwave imaging: principles and applications[J]. SCIENCE CHINA Information Sciences, 2012, 55(8): 1722-1754.
[12]	Ender J H G. On compressive sensing applied to radar[J]. Signal Processing, 2010, 90(5): 1402-1414.
[13]	Cetin M. Feature-enhanced synthetic aperture radar imaging[D].
[14]	[博士论文], University of Salford, Manchester, 2001.

施引文献

期刊类型引用(4)

1.	饶云华，潘登，朱华梁，万显荣，易建新，龚子平，柯亨玉. 基于一次反射的室内WiFi辐射源单站定位方法. 太赫兹科学与电子信息学报. 2021(04): 672-677 . 百度学术
2.	何振宇，陈武，杨扬. GPS天-地无源双基地雷达探测海面移动目标. 测绘学报. 2020(12): 1523-1534 . 百度学术
3.	周明章，姚广涛，孙海信，陈清峰，齐洁，古叶. WiFi信号外辐射源雷达双目标检测的研究. 舰船电子对抗. 2016(02): 1-4+33 . 百度学术
4.	杨小琪，姜卫东，霍凯. 基于OFDM信号的无源雷达干扰抑制方法. 雷达科学与技术. 2016(04): 364-370 . 百度学术