volume | PIER Journals

2017-01-27

Direct Application of Excitation Matrix as Sparse Transform for Analysis of Wide Angle EM Scattering Problems by Compressive Sensing

Xin-Yuan Cao,

Dr. Xin-Yuan Cao

School of Electronics and Information Engineering

Hefei Normal University

China

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Ming Sheng Chen,

Dr. Ming Sheng Chen

School of Electronics and Information Engineering

Hefei Normal University

China

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Meng Kong,

Dr. Meng Kong

School of Electronics and Information Engineering

Hefei Normal University

China

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Liang Zhang,

Dr. Liang Zhang

School of Electronics and Information Engineering

Hefei Normal University

China

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Xian-Liang Wu,

Dr. Xian-Liang Wu

Anhui University

China

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Xiangxiang Liu,

Dr. Xiangxiang Liu

School of Electronics and Information Engineering

Hefei Normal University

China

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Liangliang Cheng,

Dr. Liangliang Cheng

School of Electronics and Information Engineering

Hefei Normal University

China

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Qi Qi,

Dr. Qi Qi

School of Electronics and Information Engineering

Hefei Normal University

China

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Bingbing Chen

Dr. Bingbing Chen

School of Electronics and Information Engineering

Hefei Normal University

China

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Progress In Electromagnetics Research Letters, Vol. 65, 131-137, 2017

doi:10.2528/PIERL16112802

Abstract

When compressive sensing was employed to solve electromagnetic scattering problems over wide incident angles, the selection of sparse transform strongly affects the efficiency of the CS algorithm. Different sparse transforms will require different numbers of measurement. Thus, constructing a highly efficient sparse transform is the most important work for the CS-based electromagnetic scattering computing. Based on the linear relation between current and excitation vectors over wide incident angles, we adopt the excitation matrix as sparse transform directly to obtain a suitable sparse representation of the induced currents. The feasibility and basic principle of the algorithm are elaborated in detail, and the performance of the proposed sparse transform is validated in numerical results.

Citation

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Xin-Yuan Cao, Ming Sheng Chen, Meng Kong, Liang Zhang, Xian-Liang Wu, Xiangxiang Liu, Liangliang Cheng, Qi Qi, and Bingbing Chen, "Direct Application of Excitation Matrix as Sparse Transform for Analysis of Wide Angle EM Scattering Problems by Compressive Sensing," Progress In Electromagnetics Research Letters, Vol. 65, 131-137, 2017.
doi:10.2528/PIERL16112802

References

1. Yu, J. J. and X. Q. Sheng, "Scattering from 3-D targets in the subsurface using MOM," Journal of Electronics and Information Technology, Vol. 28, No. 5, 950-954, 2006.

2. Giuseppe, S. P., Finite Elements for Wave Electromagnetics Methods and Techniques, IEEE Press, 1994.

3. Ge, D. B. and Y. B. Yan, Finite-difference Time-domain Method for Electromagnetic Waves, Xidian University Press, 2011.

4. Yoshida, K., N. Nishimura, et al. "Application of new fast multipole boundary integral equation method to crack problems in 3D," Engineering Analysis with Boundary Elements, Vol. 25, No. 3, 239-247, 2001.
doi:10.1016/S0955-7997(01)00030-3

5. Song, J. M., C. C. Lu, and W. C. Chew, "Multilevel fast multipole algorithm for electromagnetic scattering by large complex objects," IEEE Transactions on Antennas and Propagation, Vol. 45, No. 10, 1488-1493, 1997.
doi:10.1109/8.633855

6. Ewe, W. B., L. W. Li, et al. "AIM analysis of scattering and radiation by arbitrary surface-wire configurations," IEEE Transactions on Antennas and Propagation, Vol. 55, No. 1, 162-166, 2007.
doi:10.1109/TAP.2006.888450

7. Donoho, D. L., "Compressed sensing," IEEE Transactions on Information Theory, Vol. 52, No. 4, 1289-1306, 2006.
doi:10.1109/TIT.2006.871582

8. Chen, M. S., F. L. Liu, H. M. Du, and X. L. Wu, "Compressive sensing for fast analysis of wide-angle monostatic scattering problems," IEEE Antennas and Wireless Propagation Letters, Vol. 10, No. 3, 1243-1246, 2011.
doi:10.1109/LAWP.2011.2174190

9. Cao, X. Y., M. S. Chen, M. Kong, L. Zhang, and X. L. Wu, "Method of moments based on prior knowledge for solving wide angle EM scattering problems," Chinese Physics Letters, Vol. 31, No. 11, 118401, 2014.
doi:10.1088/0256-307X/31/11/118401

10. Cai, T. T. and L. Wang, "Orthogonal matching pursuit for sparse signal recovery with noise," IEEE Transactions on Information Theory, Vol. 57, No. 7, 4680-4688, 2011.
doi:10.1109/TIT.2011.2146090