Fast Calculate Bistatic RCS Using Compressive Sensing and Characteristic Basis Function Method

被引:0
|
作者
Li, Chenlu [1 ]
Wang, Zhonggen [2 ]
Chen, Zhenzhen [3 ]
机构
[1] Hefei Normal Univ, AnHui Prov Key Lab Simulat & Design Elect Informa, Hefei 230601, Peoples R China
[2] Anhui Univ Sci & Technol, Huainan 232001, Peoples R China
[3] Hefei Univ, Hefei 230000, Peoples R China
来源
2022 INTERNATIONAL CONFERENCE ON MICROWAVE AND MILLIMETER WAVE TECHNOLOGY (ICMMT) | 2022年
关键词
D O I
10.1109/ICMMT55580.2022.10023450
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, the sparse basis in Compressive Sensing (CS) is constructed by the characteristic basis functions (CBFs) when dealing with the bistatic scattering problems. The matrix consisting of primary and secondary CBFs are naturally sparse, thus it is regarded as the sparse transform matrix. Then it is used to construct a undetermined equation to solve the weighting coefficient. The surface induced current is recovered efficiently by the OMP algorithm. The results of the bistatic RCS calculation of a conductor target with a structure like a bullet by the proposed method are consistent with that of the MoM, the accuracy of CS-CBFs is demonstrated.
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页数:2
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