Scattering center modeling for low-detectable targets

doi:10.23919/JSEE.2022.000051

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (3): 511-521.doi: 10.23919/JSEE.2022.000051

收稿日期:2020-12-22 出版日期:2022-06-18 发布日期:2022-06-24

Scattering center modeling for low-detectable targets

Yanxi CHEN(), Kunyi GUO*(), Guangliang XIAO(), Xinqing SHENG()

¹ Institute of Radio Frequency Technology and Software, School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China

Received:2020-12-22 Online:2022-06-18 Published:2022-06-24
Contact: Kunyi GUO E-mail:cyx_bit@126.com;guokunyi@bit.edu.cn;20111462@bit.edu.cn;xsheng@bit.edu.cn
About author:|CHEN Yanxi was born in 1994. He received his B.S. degree from Beijing Institute of Technology, Beijing, China, in 2017. He is currently a Ph.D. degree candidate in Beijing Institute of Technology. His major research interests include radar scattering center and electromagnetic simulation and application. E-mail: cyx_bit@126.com||GUO Kunyi was born in 1976. She received her Ph.D. degree from Chinese Academy of Sciences, Beijing, China, in 2005. She is currently a professor with the School of Information and Electronics, Beijing Institute of Technology, Beijing. Her current research interests include electromagnetic scattering, antenna propagation, scattering center modeling, and radar signal processing. E-mail: guokunyi@bit.edu.cn||XIAO Guangliang was born in 1992. He received his B.S. degree from Beijing Institute of Technology in 2016. He is currently a Ph.D. degree candidate in Beijing Institute of Technology. His major research interests include radar target character and electromagnetic simulation and application. E-mail: 20111462@bit.edu.cn||SHENG Xinqing was born in 1968. He received his B.S., M.S., and Ph.D. degrees from University of Science and Technology of China, Hefei, China, in 1991, 1994, and 1996, respectively. He is currently a chair professor of the School of Information and Electronic, Beijing Institute of Technology, Beijing, China. His current research interests include computational electromagnetics, target electromagnetic characteristics and stealth design, and complex electromagnetic environment simulation. E-mail: xsheng@bit.edu.cn
Supported by:
This work was supported by the National Key R&D Program of China (2017YFB0202500), and the National Natural Science Foundation of China (61771052).

摘要/Abstract

Abstract:

The scattering centers (SCs) of low-detectable targets (LDTs) have a low scattering intensity. It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs with strong scattering contributions. This paper presents an SC modeling approach to acquire the weak SCs of LDTs. We employ the induced currents at the LDT to search SCs, and the joint time-frequency transform together with the Hough transform to separate the scattering contributions of different SCs. Particle swarm optimization (PSO) is applied to improve the estimation results of SCs. The accuracy of the SC model built by this approach is verified by a full-wave numerical method. The validation results show that the SC model of the LDT can precisely simulate the signatures of high-resolution images, such as high-resolution range profile and inverse synthetic aperture radar (ISAR) images.

Key words: low-detectable target (LDT), stealth target, scattering center (SC) model, time-frequency representation, full-wave method

. [J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 511-521.

Yanxi CHEN, Kunyi GUO, Guangliang XIAO, Xinqing SHENG. Scattering center modeling for low-detectable targets[J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 511-521.

图/表 20

参考文献 32

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Condition	Similarity of TFR images/%	Number of iterations that tend to converge	Time cost/ min
No upper and lower limits, estimate all parameters	82	72	1008
With upper and lower limits, estimate all parameters	84	30	420
With upper and lower limits, exclude partially identifiable parameters	84	24	360

Objective function used (normalized)	Similarity of TFR images/%	RMSE of RCS	Number of iterations that tend to converge
A: Similarity of TFR images	84	4.75	24
B: RMSE of RCS	79	4.42	18
A×B	83	4.58	27
A+B	82	4.42	25
2×A+B	82	4.43	20
3×A+B	82	4.44	18

Scattering center modeling for low-detectable targets

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