Fast analysis of multi-static scattering problems with compressive sensing technique

Author(s):  
Shui-Rong Chai ◽  
Li-Xin Guo ◽  
Ke Li ◽  
Xiao Meng ◽  
Long Li
2011 ◽  
Vol 10 ◽  
pp. 1243-1246 ◽  
Author(s):  
Ming Sheng Chen ◽  
Fa Lin Liu ◽  
Hong Mei Du ◽  
Xian Liang Wu

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Meng Kong ◽  
Ming-Sheng Chen ◽  
Xin-Yuan Cao ◽  
Xian-Liang Wu

To reduce the computing resource of full-scale impedance matrix and its high-order derivatives in traditional Asymptotic Waveform Evaluation (AWE), compressive sensing (CS) is applied to AWE for fast and accurate frequency-sweep analysis of electromagnetic scattering problems. In CS framework, some prior knowledge is extracted by constructing and solving undetermined equation of 0-order surface induced current, so that coefficients about high-order induced current can be accurately obtained by the prior knowledge, and finally the wide-band radar cross section (RCS) is calculated. Numerical results of two-dimensional objects and bodies of revolution (BOR) were presented to the show the efficiency of the proposed method.


2020 ◽  
Vol 57 (19) ◽  
pp. 191405
Author(s):  
齐琦 Qi Qi ◽  
曹欣远 Cao Xinyuan ◽  
陈明生 Chen Mingsheng ◽  
刘艺 Liu Yi ◽  
况晓静 Kuang Xiaojing ◽  
...  

Radio Science ◽  
1999 ◽  
Vol 34 (4) ◽  
pp. 759-772 ◽  
Author(s):  
Bin Hu ◽  
Weng Cho Chew ◽  
Eric Michielssen ◽  
Junsheng Zhao

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
M. T. Bevacqua ◽  
L. Di Donato

Total Variation and Compressive Sensing (TV-CS) techniques represent a very attractive approach to inverse scattering problems. In fact, if the unknown is piecewise constant and so has a sparse gradient, TV-CS approaches allow us to achieve optimal reconstructions, reducing considerably the number of measurements and enforcing the sparsity on the gradient of the sought unknowns. In this paper, we introduce two different techniques based on TV-CS that exploit in a different manner the concept of gradient in order to improve the solution of the inverse scattering problems obtained by TV-CS approach. Numerical examples are addressed to show the effectiveness of the method.


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