基于多径模型的建筑区SAR三维成像中非视距目标重定位方法

林雨青; 仇晓兰; 彭凌霄; 李杭; 丁赤飚

doi:10.12000/JR24057

基于多径模型的建筑区SAR三维成像中非视距目标重定位方法

DOI: 10.12000/JR24057

林雨青^{1, 2, 3},
仇晓兰^{1, 2, 4, 5, ,},
彭凌霄^{4, 5},
李杭^{4, 5},
丁赤飚^{1, 2}

1.
中国科学院空天信息创新研究院北京 100190
2.
微波成像全国重点实验室北京 100190
3.
中国科学院大学电子电气与通信工程学院北京 100094
4.
苏州空天信息研究院苏州 215123
5.
苏州市微波成像处理与应用技术重点实验室苏州 215123

基金项目: 国家自然科学基金重大项目(61991421, 61991424, 61991420)

详细信息

作者简介:
林雨青，博士生，主要研究方向为SAR三维成像处理、多径利用雷达等

仇晓兰，研究员，博士生导师，主要研究方向为SAR成像处理、SAR图像理解

彭凌霄，助理研究员，主要研究方向为SAR图像信息处理和应用、SAR仿真技术

李　杭，副研究员，主要研究方向为阵列干涉SAR成像处理

丁赤飚，研究员，博士生导师，中国科学院院士，主要研究方向为合成孔径雷达、遥感信息处理和应用系统等

通讯作者:
仇晓兰 qiuxl@aircas.ac.cn

责任主编：罗迎 Corresponding Editor: LUO Ying
中图分类号: TN957.52
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- 被引次数: 0
出版历程
- 收稿日期: 2024-04-01
- 修回日期: 2024-05-06
- 网络出版日期: 2024-06-12
- 刊出日期: 2024-08-28

Non-line-of-sight Target Relocation by Multipath Model in SAR 3D Urban Area Imaging

LIN Yuqing^{1, 2, 3},
QIU Xiaolan^{1, 2, 4, 5
, ,},
PENG Lingxiao^{4, 5},
LI Hang^{4, 5},
DING Chibiao^{1, 2}

1.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
2.
National Key Laboratory of Microwave Imaging, Beijing 100190, China
3.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100094, China
4.
Suzhou Aerospace Information Research Institute, Suzhou 215123, China
5.
Suzhou Key Laboratory of Microwave Imaging, Processing and Application Technology, Suzhou 215123, China

Funds: The National Natural Science Foundation of China (61991421, 61991424, 61991420)

More Information

Corresponding author: QIU Xiaolan, qiuxl@aircas.ac.cn

摘要

摘要: 随着合成孔径雷达(SAR)系统小型化技术、SAR三维成像技术的发展，当前已可利用无人机载小型化阵列干涉SAR实现城区三维成像，在城市测绘、复杂环境重建等领域具有重要应用前景。然而，SAR进行城市场景三维成像时，回波中存在多径信号，会导致成像结果解译困难，却也给非视距区域隐蔽目标的发现提供了重要手段。为此，该文针对低空无人机载阵列干涉SAR建筑区三维成像中的非视距目标进行了研究，建立了非视距目标在低空阵列干涉三维成像下的多径模型，给出了城市峡谷区域利用多径扩大可视范围的计算方法，并基于建筑平面拟合提出了非视距目标重定位方法。无人机载阵列干涉SAR的仿真和实际数据处理验证表明，所提出的方法可以对城市峡谷非视距目标进行有效的三维成像和重定位，重定位误差小于0.5 m，实现了对非视距区域信息的获取。
- 阵列干涉SAR /
- 三维成像 /
- 非视距 /
- 多径 /
- 无人机载SAR
Abstract: The advancement in the miniaturization technology of Synthetic Aperture Radar (SAR) systems and SAR three-dimensional (3D) imaging has enabled the 3D imaging of urban areas through Unmanned Aerial Vehicle (UAV)-borne array Interferometric SAR (array-InSAR), offering significant utility in urban cartography, complex environment reconstruction, and related domains. Despite the challenges posed by multipath signals in urban scene imaging, these signals serve as a crucial asset for imaging hidden targets in Non-Line-of-Sight (NLOS) areas. Hence, this paper studies NLOS targets in UAV-borne array-InSAR 3D imaging at low altitudes and establishes a multipath model for 3D imaging at low altitudes. Then, a calculation method is proposed for obtaining the multipath reachable range in urban canyon areas based on building plane fitting. Finally, a relocation method for NLOS targets is presented. The simulation and real data experiments of UAV-borne array-InSAR show that the proposed method can effectively obtain 3D images and relocate NLOS targets in urban canyon areas, with errors typically below 0.5 m, which realizes the acquisition of hidden NLOS region information.
- Array-InSAR /
- 3D imaging /
- Non-Line-of-Sight (NLOS) /
- Multipath /
- UAV-borne SAR

HTML全文

图 1 城市场景下非视距场景示意图

Figure 1. Schematic diagram of the NLOS scene in an urban scenario

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图 2 阵列干涉SAR三维成像非视距目标重定位流程框图

Figure 2. Flowchart of NLOS target relocation in array-InSAR 3D imaging

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图 3 城市场景阵列干涉SAR成像模型

Figure 3. Array-InSAR imaging model for urban scene

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图 4 城市场景下非视距范围示意图

Figure 4. Schematic diagram of the NLOS range in urban scenarios

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图 5 非视距多径可达区域计算流程图

Figure 5. Flowchart for calculating the NLOS multipath reachable area

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图 6 仿真及实际实验参数示意图

Figure 6. Schematic of simulation and real data experiment parameters

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图 7 建筑物仿真实验三维点云

Figure 7. 3D point cloud of the urban canyon in simulation experiment

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图 8 单NLOS目标仿真实验三维点云对比图

Figure 8. Comparison of 3D point cloud for single NLOS target simulation experiment

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图 9 多NLOS目标仿真实验三维点云对比图

Figure 9. Comparison of 3D point cloud for multiple NLOS target simulation experiment

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图 10 MV3DSAR系统和实验场景说明

Figure 10. Illustration of the MV3DSAR system and experimental scenarios

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图 11 天津临港商务大楼SAR成像结果

Figure 11. SAR imaging results of Lingang Business Building

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图 12 天津实验SAR三维成像点云对比

Figure 12. Comparison of the SAR 3D imaging point clouds in Tianjin

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图 13 天津实验SAR三维成像点云俯视图对比

Figure 13. Comparison of the top view of the SAR 3D imaging point clouds in Tianjin

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图 14 苏州东西飞角反放置图以及实验现场图

Figure 14. Placement of multipath reflectors and experimental scene of the east-west flight in Suzhou

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图 15 苏州实验图和二维结果对应图

Figure 15. Optical image of Suzhou experiment and the corresponding 2D results

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图 16 苏州园区东西飞行多径示意图

Figure 16. Multipath diagram of east-west flight in Suzhou

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图 17 苏州东西飞行SAR三维成像结果

Figure 17. SAR 3D imaging results of east-west flights in Suzhou

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表 1 MV3DSAR实验参数(Ku波段)

Table 1. Parameters of the MV3DSAR experiment (Ku-band)

参数	指标
中心频率	15.2 GHz
信号形式	调频连续波(FMCW)
极化方式	全极化
信号带宽	1200 MHz
天线尺寸(单通道)	0.05 m(俯仰)×0.32 m(方位)
分辨率	优于0.2 m×0.2 m
中心视角	45°

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表 2 平面拟合和成像位置误差分析(m)

Table 2. Plane fitting and imaging position error analysis (m)

分析对象	ME	RMSE
楼面拟合	5.87E–13	0.6982
峡谷长度拟合	0.3328	/
非视距角反1	0.43	0.4201
非视距角反2	0.41	0.4201

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