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2021-05-28
A Prior Parameter Extraction Method for the Solution of Wide-Angle Electromagnetic Scattering Problems Based on Compressed Sensing
By
Progress In Electromagnetics Research M, Vol. 102, 207-215, 2021
Abstract
A fast solution for electromagnetic (EM) scattering problems over a wide incident angle based on compressed sensing (CS) has been proposed in recent years. Since current expansion coefficients are not known in advance, the parameters of this solution (e.g., the times of measurements, the selection of sparse transforms) for different scattering objects are difficult to determine. In order to solve this problem, this paper presents a prior parameter extraction method based on the principle of on-surface discretized boundary equation (OS-DBE), in which an approximate distribution of current expansion coefficients at any given point of the scatterer is first obtained with low-coverage and low-complexity, and then the prior parameters can be determined by CS tests for the approximate result. The implementation method is elaborated, and its effectiveness is verified by numerical results.
Citation
Daoping Wang Ming Sheng Chen Xin-Yuan Cao Qi Qi Xiangxiang Liu Chundong Hu , "A Prior Parameter Extraction Method for the Solution of Wide-Angle Electromagnetic Scattering Problems Based on Compressed Sensing," Progress In Electromagnetics Research M, Vol. 102, 207-215, 2021.
doi:10.2528/PIERM21020103
http://www.jpier.org/PIERM/pier.php?paper=21020103
References

1. Harrington, R. F., Field Computation by Moment Method, IEEE Press, New York, 1993.

2. Song, J., 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

3. Catedra, M. F., F. Ruiz, and E. Gago, "Analysis of arbitrary metallic surfaces conformed to a circular cylinder using the conjugate gradient-fast Fourier transform (CG-FFT) method," IEEE Transactions on Antennas and Propagation, Vol. 38, No. 2, 286-289, 1990.
doi:10.1109/8.45135

4. Bleszynski, E., M. Bleszynski, and T. Jaroszewicz, "AIM: Adaptive integral method for solving large-scale electromagnetic scattering and radiation problems," Radio Science, Vol. 31, No. 5, 1225-1251, 1996.
doi:10.1029/96RS02504

5. Zhao, K. Z., M. N. Vouvakis, and J. F. Lee, "The adaptive cross approximation algorithm for accelerated method of moments computations of EMC problems," IEEE Transactions on Electromagnetic Compatibility, Vol. 47, No. 4, 763-773, 2005.
doi:10.1109/TEMC.2005.857898

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

7. 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

8. Chai, S. R. and L. X. Guo, "Compressive sensing for monostatic scattering from 3-D NURBS geometries," IEEE Transactions on Antennas and Propagation, Vol. 64, No. 8, 3545-3553, 2016.
doi:10.1109/TAP.2016.2580166

9. Xu, Y. S. and K. Wang, "Discretized boundary equation method for two-dimensional scattering problems," IEEE Transactions on Antennas and Propagation, Vol. 55, No. 12, 3550-3564, 2007.
doi:10.1109/TAP.2007.910305

10. Tropp, J. A. and A. C. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit," IEEE Transactions on Information Theory, Vol. 53, No. 12, 4655-4666, 2007.
doi:10.1109/TIT.2007.909108

11. Tang, F. S. and Y. S. Xu, "Iterative on-surface discretized boundary equation method for 2-D scattering problems," IEEE Transactions on Antennas and Propagation, Vol. 60, No. 11, 5187-5194, 2012.
doi:10.1109/TAP.2012.2208257

12. Cao, X.-Y., M. S. Chen, M. Kong, L. Zhang, X.-L. Wu, X. Liu, L. Cheng, Q. Qi, and B. 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