Space-mapping Inspired Scattering Model Construction Based on Sparse Representation

被引:0
|
作者
Yan, Tianxu [1 ]
Li, Dongying [1 ]
Yu, Wenxian [1 ]
机构
[1] Shanghai Jiao Tong Univ, Shanghai Key Lab Intelligent Sensing & Recognit, Shanghai, Peoples R China
关键词
Space mapping; surrogate model; sparse representation; parameter; OPTIMIZATION; IMPLICIT;
D O I
暂无
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
A space-mapping inspired scattering construction method is proposed based on sparse representation for extended targets. Differing from the conventional space mapping technique of which the goal is to optimize the design parameters given an optimization target, the space mapping technique is modified to build a surrogate model by mapping the sparse representation of scattering response from the coarse model and the fine model. A robust and accurate method based on the particle swarm optimization is designed to extract the parameters of the basis function of the sparse representation of both the coarse model and the fine model. After that, a space-mapping optimization is run to extract the mapping matrix between the two sparse models. The simulation result shows that the extracted model not only has a much better accuracy than the conventional asymptotic model but also works effectively over a considerable range of the scatterer parameter space.
引用
收藏
页码:357 / 360
页数:4
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