NEAR-FIELD 3D SAR INTERPRETATION BASED ON LIDAR AND SAR CALIBRATION

被引:0
作者
Wang, Baoyou [1 ]
Zhang, Xiaoling [1 ]
Shi, Jun [1 ]
Wei, Shunjun [1 ]
Zeng, Tianjiao [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Peoples R China
来源
IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2023年
关键词
near-field array 3D SAR; Lidar; calibration; scattering diagnosis;
D O I
10.1109/IGARSS52108.2023.10282562
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The near-field array three-dimensional SAR can obtain the three-dimensional electromagnetic scattering characteristics of targets and present the imaging results in the form of point cloud. In recent years, it has been gradually used in the field of target RCS measurement. However, there are some problems in near-field array three-dimensional SAR images, such as interference, sidelobe and missing of target shape. Lidar has the characteristics of high positioning accuracy and strong target shape description. The fusion of Lidar with the near-field array three-dimensional SAR can effectively assist the scattering characteristic diagnosis of SAR images, in which the calibration plays an important role. This paper presents a calibration method for Lidar and near-field array three-dimensional SAR. The method is divided into three steps of calibration target design, extraction and alignment. By designing a special calibration target, correcting the imaging position deviation of Lidar, and converting the problem of calibration corresponding point selection into a problem of matching target set, the coordinate system of Lidar and SAR can be aligned. The effectiveness of the proposed method is verified by the experimental results of measured data.
引用
收藏
页码:5918 / 5921
页数:4
相关论文
共 9 条
[1]   Use of a Plane-Wave Synthesis Technique to Obtain Target RCS From Near-Field Measurements, With Selective Feature Extraction Capability [J].
Ford, Kenneth L. ;
Bennett, John C. ;
Holtby, Daniel G. .
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2013, 61 (04) :2051-2057
[2]   Doppler Division Multiplexed Multiple-Input-Multiple-Output Imaging Using Cascaded Millimeter-Wave Radars [J].
Kitamura, Takayuki ;
Suwa, Kei .
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2022, 70 (03) :1571-1581
[3]   Extrinsic and Temporal Calibration of Automotive Radar and 3D LiDAR [J].
Lee, Chia-Le ;
Hsueh, Yu-Han ;
Wang, Chieh-Chih ;
Lin, Wen-Chieh .
2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, :9976-9983
[4]   Accurate and Automatic Extrinsic Calibration for a Monocular Camera and Heterogenous 3D LiDARs [J].
Li, Xingxing ;
He, Feiyang ;
Li, Shengyu ;
Zhou, Yuxuan ;
Xia, Chunxi ;
Wang, Xuanbin .
IEEE SENSORS JOURNAL, 2022, 22 (16) :16472-16480
[5]  
Li Y, 2020, 2020 IEEE 5TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION ENGINEERING (IEEE ICITE 2020), P456, DOI [10.1109/ICITE50838.2020.9231446, 10.1109/icite50838.2020.9231446]
[6]   Point Set Registration: Coherent Point Drift [J].
Myronenko, Andriy ;
Song, Xubo .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2010, 32 (12) :2262-2275
[7]  
Persic J, 2017, 2017 EUROPEAN CONFERENCE ON MOBILE ROBOTS (ECMR)
[8]   Three-Dimensional Microwave Imaging for Concealed Weapon Detection Using Range Stacking Technique [J].
Tan, Weixian ;
Huang, Pingping ;
Huang, Zengshu ;
Qi, Yaolong ;
Wang, Wenqin .
INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION, 2017, 2017
[9]   MLESAC: A new robust estimator with application to estimating image geometry [J].
Torr, PHS ;
Zisserman, A .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2000, 78 (01) :138-156