Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

doi:10.23919/JSEE.2021.000098

Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (5): 1143-1151.doi: 10.23919/JSEE.2021.000098

收稿日期:2020-07-27 出版日期:2021-10-18 发布日期:2021-11-08

Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

Kai ZHOU^1,², Daojing LI^1,*(), Anjing CUI^1,²(), Dong HAN^1,²(), He TIAN³(), Haifeng YU⁴(), Jianbo DU⁴(), Lei LIU⁴(), Yu ZHU⁴(), Running ZHANG⁴()

¹ National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100190, China
² School of Electronic, Electrical and Communication Engineening, University of Chinese Academy of Sciences, Beijing 100049, China
³ Science and Technology on Electromagnetic Scattering Laboratory, Beijing Institute of Environmental Features, Beijing 100854, China
⁴ General Design Department, China Academy of Space Technology, Beijing 100094, China

Received:2020-07-27 Online:2021-10-18 Published:2021-11-08
Contact: Daojing LI E-mail:lidj@mail.ie.ac.cn;ajcui@qq.com;handong17@mails.ucas.edu.cn;tianhe0407@126.com;castyu2@126.com;jianbodu.sky@outlook.com;liulei211@163.com;zhuyubit@163.com;13661051645@139.com
About author:|ZHOU Kai was born in 1995. He received his B.S. degree in electronic information science and technology from Central South University, Changsha, Hunan, China in 2018. He is currently pursing his Ph.D. degree in Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. His research interests include synthetic aperture lidar signal processing, sparse flight 3-D imaging, and infrared target detection, etc. E-mail: zk_6810@163.com||LI Daojing was born in 1964. He received his B.S. and M.S. degrees in communication and electronic systems from Nanjing University of Science and Technology in 1986 and 1991. From 1986 to 2006, he was engaged in the research of ground radar in Xi’an Electronic Engineering Institute. In 2003, he received his Ph.D. degree in circuit and system from Northwestern Polytechnical University. In 2006, he joined the Institute of Electrics, Chinese Academy of Sciences. At present, he is a professor and doctoral supervisor in Science and Technology on Microwave Imaging Laboratory, Aerospace Information Research Institute, Chinese Academy of Sciences, his main research interests include radar system and radar signal processing. E-mail: lidj@mail.ie.ac.cn||CUI Anjing was born in 1997. She received her B.S. degree in electronic information engineering from Xidian University, Xi’an, Shaanxi, China in 2020. She is currently pursing her Ph.D. degree in Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. Her research interests include array antenna and signal processing. E-mail: ajcui@qq.com||HAN Dong was born in 1994. He received his B.S. degree in automation from University of Science and Technology of China, Hefei, China, in 2017. He is currently pursuing his Ph.D. degree in signal and information processing in University of Chinese Academy of Sciences, Beijing, China. His research interests include SAR tomography and holography. E-mail: handong17@mails.ucas.edu.cn||TIAN He was born in 1991. She received her Ph.D. degree in Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China in 2018. At present, she is an engineer in Science and Technology on Electromagnetic Scattering Laboratory, Beijing Institute of Environmental Features, Beijing, China. Her research interests include radar signal processing, radar imaging recognition and target characteristics. E-mail: tianhe0407@126.com||YU Haifeng was born in 1978. He is a researcher in the General Design Department, China Academy of Space Technology, Beijing, China. His research interests include microwave remote sensing. E-mail: castyu2@126.com||DU Jianbo was born in 1991. He received his Ph.D. degree in Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China in 2017. At present, he is an engineer in the General Design Department, China Academy of Space Technology, Beijing, China. His research interests include spacecraft system engineering and radar signal processing. E-mail: jianbodu.sky@outlook.com||LIU Lei was born in 1985. He is a senior engineer in the General Design Department, China Academy of Space Technology, Beijing, China. His research interests include microwave remote sensing. E-mail: liulei211@163.com||ZHU Yu was born in 1978. He is a researcher in the General Design Department, China Academy of Space Technology, Beijing, China. His research interests include microwave remote sensing. E-mail: zhuyubit@163.com||ZHANG Running was born in 1966. He is a researcher in the General Design Department, China Academy of Space Technology, Beijing, China. His research interests include microwave remote sensing. E-mail: 13661051645@139.com
Supported by:
This work was supported by the General Design Department, China Academy of Space Technology (10377).

摘要/Abstract

Abstract:

The spaceborne synthetic aperture radar (SAR) sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture, and achieve the third dimensionality recognition. In this paper, combined with the actual triple star orbits, a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis (PCA) is presented. Firstly, interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain. Secondly, as a method with simple principle and fast calculation, the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics. Finally, the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA. The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49% and random noise introduced by the receiver. Meanwhile, due to the influence of orbit distribution of the actual triple star orbits, the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results. This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.

Key words: principal component analysis (PCA), spaceborne synthetic aperture radar (SAR), sparse flight, sparse spectrum by interferometry, 3-D imaging

. [J]. Journal of Systems Engineering and Electronics, 2021, 32(5): 1143-1151.

Kai ZHOU, Daojing LI, Anjing CUI, Dong HAN, He TIAN, Haifeng YU, Jianbo DU, Lei LIU, Yu ZHU, Running ZHANG. Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis[J]. Journal of Systems Engineering and Electronics, 2021, 32(5): 1143-1151.

图/表 12

参考文献 30

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Parameter	Value
Wave length $\lambda $ /m	0.03
System bandwidth $B$ /MHz	150
Reference platform height $H$ /km	500
Incident angle $\theta $ /(°)	30
Spaceborne platform speed $V$ /(km/s)	7
Minimum sampling interval ${d_{\min }}$ /m	110
Equivalent aperture length of cross-track ${L_s}$ /km	4.84
Theoretical cross-track resolution ${\rho _s}$ /m	1.78
Unambiguous range of cross-track ${s_{\max }}$ /m	79
Actual range ${\rho _r}$ /m	1
Actual azimuth resolution ${\rho _a}$ /m	2.2
Sparse flight orbit times	23/24
Multiple of cross-track up-sampling	64

Sparse flight mode	Algorithm	SNR of echo/dB	RMSE/m
7BCO	DI	—	0.402 2
7BCO	IPCA	—	0.348 3
ATSO	DI	—	0.469 2
ATSO	IPCA	—	0.433 7
ATSO	DI	?36	0.480 7
ATSO	IPCA	?36	0.448 8

Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

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