Systems Engineering and Electronics ›› 2020, Vol. 42 ›› Issue (12): 2716-2734.doi: 10.3969/j.issn.1001-506X.2020.12.07
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Jianfeng ZHANG(), Yaowen FU(
), Wenpeng ZHANG(
), Wei YANG(
), Tao LI(
)
Received:
2020-04-17
Online:
2020-12-01
Published:
2020-11-27
CLC Number:
Jianfeng ZHANG, Yaowen FU, Wenpeng ZHANG, Wei YANG, Tao LI. Review of CSAR imaging techniques[J]. Systems Engineering and Electronics, 2020, 42(12): 2716-2734.
Table 1
Research progress of CSAR abroad"
时间/年 | 研究单位 | 研究内容 | 研究结果 |
1996 | 美国纽约州立大学 | CSAR成像模式初步探索 | CSAR成像回波信号模型 |
1998 | 美国华盛顿大学 | CSAR分辨率分析 | CSAR具有三维高分辨成像潜力 |
2001 | 美国佐治亚理工学院雷达研究所 | E-CSAR成像系统转台实验 | 验证了CSAR成像原理 |
2004 | 瑞典国防研究局 | VHF波段CARABAS-II雷达系统CSAR机载实验 | CSAR可提高对地面目标的检测性能 |
2006 | AFRL | X波段全极化多航过CSAR机载试验 | CSAR具有高分辨成像、目标检测潜力 |
ONERA | X波段机载CSAR试验 | 验证了CSAR成像可行性 | |
2007 | ONERA | 多波段猎鹰-20机载CSAR试验 | 得到了数字高程模型, CSAR具有地形测绘潜力 |
2008 | DLR | E-SAR系统L波段全极化机载CSAR试验 | CSAR比条带SAR能获取更多的目标散射信息 |
2010 | 瑞典国防研究局 | VHF-UHF波段LORA系统机载CSAR实验 | 证实了CSAR的高检测性能 |
2012 | DLR | P波段、L波段全极化CSAR全息成像机载试验 | 验证了CSAR三维成像可行性 |
2013 | AFRL | 机载CSAR大场景成像实验 | 获得了尺寸为6 km×6 km的CSAR图像 |
ONERA | 步进频X波段RAMSES-NG系统机载CSAR试验 | 得到了飞机、汽车和卡车等目标的高分辨率图像 | |
2014 | DLR | 多输入多输出CSAR成像理论 | 多输入多输出CSAR有利于大场景高分辨成像 |
2015 | 土耳其Mersin大学 | 宽域CSAR成像实验 | CSAR三维成像过程中,目标与成像平面若不处于同一高度,将出现散焦 |
2017 | ONERA | 2 GHz信号带宽下的机载CSAR试验 | 获得了大带宽下的高分辨CSAR图像 |
2018 | 德国Ulm大学 | 多旋翼无人机载CSAR实验 | 验证了多旋翼无人机载CSAR成像的可行性 |
2019 | 德国Fraunhofer研究所 | W波机载FMCW CSAR成像试验 | W波段机载CSAR在对地高分辨观测中具有巨大潜力 |
Table 2
Research progress of domestic CSAR"
时间/年 | 研究单位 | 研究内容 | 研究结果 |
2006 | 北京航空航天大学 | 不同曲线合成孔径下的成像仿真实验 | 圆形轨迹SAR具有更好的成像效果 |
2007-2010 | IECAS | CSAR成像性能分析;三维成像能力研究;微波暗室内转台CSAR实验 | 星载平台、临近空间平台和机载平台等是实现CSAR的方向;初步验证了CSAR的实际可行性 |
2011 | IECAS | 全极化P波段CSAR机载试验 | CSAR比条带SAR能获取更精细的目标信息 |
2014 | IECAS | CSAR数据中提取建筑物轮廓信息以及估计建筑物所处地面高度的实验 | 得到了目标建筑物的轮廓信息,并将该成像平面高度确定为目标建筑物的地面高度 |
2015 | NUDT | Ku波段Mini-SAR轻型固定翼机载CSAR试验; P波段超宽带多基线CSAR机载实验 | 得到了固定翼无人机载CSAR高分辨图像;获取了多条轨迹CSAR数据 |
2017 | CETC No.38 | 线极化P波段机载CSAR试验CSAR三维图像重构实验 | CSAR比条带SAR在目标检测、识别、分类等方面更具优势目标车辆轮廓信息清晰,车辆尺寸估计精度较高 |
2018 | 西安电子科技大学 | CSAR数据场景目标数字高程模型提取实验 | CSAR能较精确地提取出观测场景中目标的数字高程模型 |
2018-2019 | NUDT | CSAR相干和非相干成像性能分析;毫米波FMCW CSAR成像性能分析; | 对于非各向同性目标,非相干成像可获取质量更好的图像; FMCW CSAR脉内平台连续运动会影响成像质量 |
2019 | IECAS | CSAR系统理论研究 | 得到了CSAR系统参数设计、成像区域选择以及方位模糊计算准则 |
2020 | 电子科技大学 | CSAR运动误差补偿技术研究 | 能补偿二维空变性的CSAR运动误差 |
Table 3
Performance comparison of CSAR imaging algorithms"
算法名称 | 优点 | 缺点 |
CSAR/FMCW CSAR BP算法 | 精度高、不受SAR运动轨迹限制、过程简单 | 计算量大、效率低 |
CSAR FFBP算法 | 成像效率比BP高 | 高波段内效率不能显著提高、插值误差 |
波前重构CSAR算法 | 效率较高 | 数据利用率低、成像场景较小、插值误差 |
NUFFT改进型波前重构CSAR算法 | 数据利用率较高、插值误差较小 | 主瓣展宽、旁瓣较高 |
改进型LP范数图像特征增强CSAR算法 | 有效降低旁瓣 | 主瓣展宽 |
子孔径CSAR频域算法 | 效率较高、成像场景较大 | 子场景图像精细拼接难度大、近似处理多误差大、高频段效率降低误差增大、可能损失目标散射信息 |
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