高分辨率星载SAR成像与图像质量提升方法综述

李春升 于泽 陈杰

李春升, 于泽, 陈杰. 高分辨率星载SAR成像与图像质量提升方法综述[J]. 雷达学报, 2019, 8(6): 717–731. doi: 10.12000/JR19085
引用本文: 李春升, 于泽, 陈杰. 高分辨率星载SAR成像与图像质量提升方法综述[J]. 雷达学报, 2019, 8(6): 717–731. doi: 10.12000/JR19085
LI Chunsheng, YU Ze, and CHEN Jie. Overview of techniques for improving high-resolution spaceborne SAR imaging and image quality[J]. Journal of Radars, 2019, 8(6): 717–731. doi: 10.12000/JR19085
Citation: LI Chunsheng, YU Ze, and CHEN Jie. Overview of techniques for improving high-resolution spaceborne SAR imaging and image quality[J]. Journal of Radars, 2019, 8(6): 717–731. doi: 10.12000/JR19085

高分辨率星载SAR成像与图像质量提升方法综述

DOI: 10.12000/JR19085
基金项目: 国家自然科学基金(61861136008)
详细信息
    作者简介:

    李春升(1963–),男,天津人,北京航空航天大学,教授,博士生导师,主要从事星载SAR系统总体与仿真、多源遥感图像信息融合、信息获取与处理等方面的研究工作。E-mail: lichunsheng@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

    陈 杰(1973–),教授、博士生导师,长期从事高分辨率微波遥感信息系统理论与方法研究。2005年获得北京市高等教育成果二等奖,2006年入选教育部“新世纪优秀人才支持计划”,2008年获霍英东教育基金会第十一届高等院校青年教师奖三等奖。承担国家自然科学基金、“973”计划、“863”计划、国家重大专项等多项课题。已发表论文100余篇,其中SCI(E)检索15篇,EI检索80余篇。申请国家发明专利20余项,合作编写教材4部,合作出版译著1部。E-mail: chenjie@buaa.edu.cn

    通讯作者:

    李春升 lichunsheng@buaa.edu.cn

    于泽 yz613@buaa.edu.cn

  • 中图分类号: TN958

Overview of Techniques for Improving High-resolution Spaceborne SAR Imaging and Image Quality

Funds: The National Natural Science Foundation of China (61861136008)
More Information
  • 摘要: 作为一种重要的空间遥感信息获取工具,星载合成孔径雷达(SAR)具备高分辨率宽测绘、多方位信息获取、高时相对地观测、3维地形测绘等多种工作体制和模式。对于任何星载SAR系统,获取高质量的图像始终是提升SAR应用效能的前提。该文基于“观测在天,成像在地”的理念,分析了卫星轨道、平台姿态、有效载荷、地面处理等环节中星载SAR成像和图像质量的影响因素;阐释了中央电子设备幅相补偿与动态调整、天线方向图预估等高精度数据获取技术;给出了基于改进运动模型的星载SAR成像补偿和对流层传播效应补偿方法,能够实现优于0.3 m分辨率的成像;总结和对比了相干斑噪声抑制、方位模糊抑制和旁瓣抑制等SAR图像处理技术,可以使得等效视数优于25、方位模糊和旁瓣抑制优于20 dB。

     

  • 图  1  星载SAR对地观测示意图

    Figure  1.  Observation geometry of spaceborne SAR

    图  2  星载SAR有效载荷基本结构示意图

    Figure  2.  Diagram of the basic structure of the spaceborne SAR payload

    图  3  MGC反演前后的成像结果

    Figure  3.  Imaging results before and after MGC inversion

    图  4  星载SAR天线系统优化和方向图预估技术示意图

    Figure  4.  Diagram of optimization and pattern estimation technology for spaceborne SAR antenna system

    图  5  停走误差补偿前后成像结果对比图

    Figure  5.  Comparison of imaging results before and after the compensation of stop-go phase error

    图  6  原始SAR图像和斑点噪声抑制后的结果

    Figure  6.  Results of speckle suppression

    图  7  方位模糊抑制效果

    Figure  7.  Azimuth ambiguity suppression result

    图  8  SVA处理结果

    Figure  8.  SVA result

    图  9  SAR图像质量提升方法总结

    Figure  9.  Summary of SAR image quality improvement methods

    表  1  实时定轨和事后定轨比较

    Table  1.   Comparison between real-time and precise orbit determination

    输入数据类型数据时效性定轨精度
    实时定轨广播星历+双频伪距
    载波观测数据
    实时米级
    事后定轨IGS最终产品+双频伪距
    载波观测数据
    12–18天厘米级
    下载: 导出CSV

    表  2  通道误差补偿前后脉冲压缩性能

    Table  2.   Performance of pulse compression before and after compensating for channel error

    幅相误差分辨率(m)展宽系数峰值旁瓣比(dB)积分旁瓣比(dB)
    无补偿0.23921.0800–6.41–5.85
    补偿0.22321.0077–13.25–9.97
    下载: 导出CSV

    表  3  仿真参数

    Table  3.   Simulation parameters

    参数数值参数数值
    轨道倾角98.06°波束宽度(方位向)0.305°
    轨道高度680 km斜视角±6.21°
    偏心率0.001信号带宽1.0 GHz
    观测视角35°脉冲宽度40 μs
    波长0.03 m脉冲重复频率4000 Hz
    下载: 导出CSV

    表  4  停走误差补偿前后成像质量评估结果

    Table  4.   Imaging quality evaluation of point target before and after compensating for stop-go error

    分辨率(m)峰值旁瓣比(dB)积分旁瓣比(dB)
    距离向补偿前0.1444–15.42–12.51
    补偿后0.1342–13.13–9.80
    方位向补偿前0.2420–11.98–9.79
    补偿后0.2170–13.32–10.41
    下载: 导出CSV

    表  5  不同视角下目标对流层延迟补偿前后对比

    Table  5.   Evaluation results before and after tropospheric delay compensation with different looking angles

    视角(°)对流层延迟补偿前方位向性能对流层延迟补偿后方位向性能
    分辨率(m)PSLR(dB)ISLR(dB)分辨率(m)PSLR(dB)ISLR(dB)
    150.272–12.448–9.2130.270–13.246–10.150
    350.272–12.033–8.9380.269–13.223–10.319
    550.294–8.579–5.8600.275–13.240–10.069
    下载: 导出CSV

    表  6  斑点噪声抑制指标

    Table  6.   Speckle noise suppression performance

    图像ENL1ENL2EPI
    图6(a)0.99960.9682
    图6(b)36.333826.30640.9484
    图6(c)1.04201.0051
    图6(d)67.272736.55820.9480
    下载: 导出CSV
  • [1] WANG Pengbo, LIU Wei, CHEN Jie, et al. A high-order imaging algorithm for high-resolution spaceborne sar based on a modified equivalent squint range model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(3): 1225–1235. doi: 10.1109/TGRS.2014.2336241
    [2] CHEN Jie, KUANG Hui, YANG Wei, et al. A novel imaging algorithm for focusing high-resolution spaceborne SAR data in squinted sliding-spotlight mode[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(10): 1577–1581. doi: 10.1109/LGRS.2016.2598066
    [3] 赵团, 邓云凯, 王宇, 等. 基于扇贝效应校正的改进滑动Mosaic全孔径成像算法[J]. 雷达学报, 2016, 5(5): 548–557. doi: 10.12000/JR16014

    ZHAO Tuan, DENG Yunkai, WANG Yu, et al. Processing sliding mosaic mode data with modified full-aperture imaging algorithm integrating scalloping correction[J]. Journal of Radars, 2016, 5(5): 548–557. doi: 10.12000/JR16014
    [4] TOWNSEND W. An initial assessment of the performance achieved by the Seasat-1 radar altimeter[J]. IEEE Journal of Oceanic Engineering, 1980, 5(2): 80–92. doi: 10.1109/JOE.1980.1145459
    [5] 李春升, 王伟杰, 王鹏波, 等. 星载SAR技术的现状与发展趋势[J]. 电子与信息学报, 2016, 38(1): 229–240.

    LI Chunsheng, WANG Weijie, WANG Pengbo, et al. Current situation and development trends of spaceborne SAR technology[J]. Journal of Electronics &Information Technology, 2016, 38(1): 229–240.
    [6] PITZ W and MILLER D. The TerraSAR-X satellite[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(2): 615–622. doi: 10.1109/TGRS.2009.2037432
    [7] DE ZAN F and GUARNIERI A M. TOPSAR: Terrain observation by progressive scans[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(9): 2352–2360. doi: 10.1109/TGRS.2006.873853
    [8] 魏钟铨. 合成孔径雷达卫星[M]. 北京: 科学出版社, 2001.

    WEI Zhongquan. Synthetic Aperture Radar Satellite[M]. Beijing: Science Press, 2001.
    [9] CURLANDER J C and MCDONOUGH R N. Synthetic Aperture Radar: Systems and Signal Processing[M]. New York: John Wiley & Sons, 1991.
    [10] PRATS-IRAOLA P, SCHEIBER R, RODRIGUEZ-CASSOLA M, et al. On the processing of very high resolution spaceborne SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(10): 6003–6016. doi: 10.1109/TGRS.2013.2294353
    [11] 万丽华, 魏立龙, 王磊. 基于全球台站的GNSS卫星精密定轨策略分析[J]. 测绘地理信息, 2019, 44(4): 53–58. doi: 10.14188/j.2095-6045.2017331

    WAN Lihua, WEI Lilong, and WANG Lei. On the strategies of precise orbit determination of GNSS from global stations[J]. Journal of Geomatics, 2019, 44(4): 53–58. doi: 10.14188/j.2095-6045.2017331
    [12] 丁赤飚, 刘佳音, 雷斌, 等. 高分三号SAR卫星系统级几何定位精度初探[J]. 雷达学报, 2017, 6(1): 11–16. doi: 10.12000/JR17024

    DING Chibiao, LIU Jiayin, LEI Bin, et al. Preliminary exploration of systematic geolocation accuracy of GF-3 SAR satellite system[J]. Journal of Radars, 2017, 6(1): 11–16. doi: 10.12000/JR17024
    [13] 秦显平. 星载GPS低轨卫星定轨理论及方法研究[D]. [博士论文], 解放军信息工程大学, 2009.

    QIN Xianping. Research on precision orbit determination theory and method of low earth orbiter based on GPS technique[D]. [Ph.D. dissertation], PLA Information Engineering University, 2009.
    [14] 崔仁洁. 卫星姿态控制一体化仿真系统设计与研究[D]. [硕士论文], 浙江大学, 2017.

    CUI Renjie. Design and research of the integrated simulation platform for satellites attitude control system[D].[Master dissertation], Zhejiang University, 2017.
    [15] LI Zhou, LI Chunsheng, YU Ze, et al. Effects of receiver saturation on image formation[C]. 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, Canada, 2011: 535–538. doi: 10.1109/IGARSS.2011.6049183.
    [16] SMITH A M. A new approach to range-Doppler SAR processing[J]. International Journal of Remote Sensing, 1991, 12(2): 235–251. doi: 10.1080/01431169108929650
    [17] JIN M Y, CHENG F, and CHEN Ming. Chirp scaling algorithms for SAR processing[C]. 1993 IEEE International Geoscience and Remote Sensing Symposium, Tokyo, Japan, 1993: 1169–1172. doi: 10.1109/IGARSS.1993.322129.
    [18] LIU Yan, XING Mengdao, SUN Guangcai, et al. Echo model analyses and imaging algorithm for high-resolution SAR on high-speed platform[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(3): 933–950. doi: 10.1109/tgrs.2011.2162243
    [19] WU Yuan, SUN Guangcai, YANG Chun, et al. Processing of very high resolution spaceborne sliding spotlight SAR data using velocity scaling[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(3): 1505–1518. doi: 10.1109/TGRS.2015.2481923
    [20] YU Ze, WANG Shusen, and LI Zhou. An imaging compensation algorithm for spaceborne high-resolution SAR based on a continuous tangent motion model[J]. Remote Sensing, 2016, 8(3): 223. doi: 10.3390/rs8030223
    [21] 胡程, 董锡超, 李元昊. 大气层效应对地球同步轨道SAR系统性能影响研究[J]. 雷达学报, 2018, 7(4): 412–424. doi: 10.12000/JR18032

    HU Cheng, DONG Xichao, and LI Yuanhao. Atmospheric effects on the performance of geosynchronous orbit SAR systems[J]. Journal of Radars, 2018, 7(4): 412–424. doi: 10.12000/JR18032
    [22] YU Ze, LI Zhou, and WANG Shusen. An imaging compensation algorithm for correcting the impact of tropospheric delay on spaceborne high-resolution SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(9): 4825–4836. doi: 10.1109/tgrs.2015.2411261
    [23] 郭小洋, 李洋, 林赟, 等. 基于CSAR成像的相干斑统计模型研究[J]. 雷达学报, 2015, 4(6): 708–714. doi: 10.12000/JR15039

    GUO Xiaoyang, LI Yang, LIN Yun, et al. Statistical models of speckle for circular SAR imaging[J]. Journal of Radars, 2015, 4(6): 708–714. doi: 10.12000/JR15039
    [24] KUAN D T, SAWCHUK A A, STRAND T C, et al. Adaptive noise smoothing filter for images with signal-dependent noise[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1985, PAMI-7(2): 165–177. doi: 10.1109/TPAMI.1985.4767641
    [25] ARGENTI F and ALPARONE L. Speckle removal from SAR images in the undecimated wavelet domain[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2363–2374. doi: 10.1109/tgrs.2002.805083
    [26] YU Yongjian and ACTON S T. Speckle reducing anisotropic diffusion[J]. IEEE Transactions on Image Processing, 2002, 11(11): 1260–1270. doi: 10.1109/TIP.2002.804276
    [27] DELEDALLE C A, DENIS L, and TUPIN F. Iterative weighted maximum likelihood denoising with probabilistic patch-based weights[J]. IEEE Transactions on Image Processing, 2009, 18(12): 2661–2672. doi: 10.1109/TIP.2009.2029593
    [28] PARRILLI S, PODERICO M, ANGELINO C V, et al. A nonlocal SAR image denoising algorithm based on LLMMSE wavelet shrinkage[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(2): 606–616. doi: 10.1109/tgrs.2011.2161586
    [29] WANG Puyang, ZHANG He, and PATEL V M. SAR image despeckling using a convolutional neural network[J]. IEEE Signal Processing Letters, 2017, 24(12): 1763–1767. doi: 10.1109/LSP.2017.2758203
    [30] ZHANG Qian, YUAN Qiangqiang, LI Jie, et al. Learning a dilated residual network for SAR image despeckling[J]. Remote Sensing, 2018, 10(2): 196. doi: 10.3390/rs10020196
    [31] WANG Puyang, ZHANG He, and VISHAL M P. Generative adversarial network-based restoration of speckled SAR images[C]. 2017 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Curacao, Netherlands, 2017: 1–5. doi: 10.1109/CAMSAP.2017.8313133.
    [32] YU Ze, WANG Wenqi, LI Chunsheng, et al. Speckle noise suppression in SAR images using a three-step algorithm[J]. Sensors, 2018, 18(11): 3643. doi: 10.3390/s18113643
    [33] 肖鹏, 吴有明, 于泽, 等. 一种基于压缩感知恢复算法的SAR图像方位模糊抑制方法[J]. 雷达学报, 2016, 5(1): 35–41. doi: 10.12000/JR16004

    XIAO Peng, WU Youming, YU Ze, et al. Azimuth ambiguity suppression in SAR images based on compressive sensing recovery algorithm[J]. Journal of Radars, 2016, 5(1): 35–41. doi: 10.12000/JR16004
    [34] MOREIRA A. Suppressing the azimuth ambiguities in synthetic aperture radar images[J]. IEEE Transactions on Geoscience and Remote Sensing, 1993, 31(4): 885–895. doi: 10.1109/36.239912
    [35] CHEN Jie, IQBAL M, YANG Wei, 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. doi: 10.1109/TGRS.2013.2279109
    [36] GUARNIERI A M. Adaptive removal of azimuth ambiguities in SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(3): 625–633. doi: 10.1109/tgrs.2004.842476
    [37] WU Youming, YU Ze, XIAO Peng, et al. Suppression of azimuth ambiguities in spaceborne SAR images using spectral selection and extrapolation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(10): 6134–6147. doi: 10.1109/TGRS.2018.2832193
    [38] 陶一凡. SAR图像旁瓣抑制和目标识别方法的研究及实现[D]. [硕士论文], 浙江工业大学, 2017.

    TAO Yifan. Research and implement on methods of SAR image sidelobe suppression and target recognition[D]. [Master dissertation], Zhejiang University of Technology, 2017.
    [39] ZHU Xiaoxiang, HE Feng, YE Fan, et al. Sidelobe suppression with resolution maintenance for SAR images via sparse representation[J]. Sensors, 2018, 18(5): 1589. doi: 10.3390/s18051589
    [40] VARSHNEY L R and THOMAS D. Sidelobe reduction for matched filter range processing[C]. Proceedings of the 2003 IEEE Radar Conference, Huntsville, USA, 2003: 446–451. doi: 10.1109/NRC.2003.1203439.
    [41] JIN Guodong, DENG Yunkai, WANG R, et al. An advanced nonlinear frequency modulation waveform for radar imaging with low sidelobe[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(8): 6155–6168. doi: 10.1109/TGRS.2019.2904627
    [42] SMITH B H. Generalization of spatially variant apodization to noninteger Nyquist sampling rates[J]. IEEE Transactions on Image Processing, 2000, 9(6): 1088–1093. doi: 10.1109/83.846250
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出版历程
  • 收稿日期:  2019-09-21
  • 修回日期:  2019-11-30
  • 网络出版日期:  2019-12-01

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