For microwave computational imaging (MCI), the reduction of measurement matrix's coherences permits better reconstruction performance. Therefore, frequency diverse apertures (FDAs) have become a major option of antennas for MCI due to their frequency-varying radiation patterns. The frequency diversity in the patterns reduces coherences; however, the losses in practical materials and the finite sizes of apertures impose upper limits on frequency diversity. For further coherence reduction, the polarization diversity (PD) of aperture elements is as a new approach introduced in this paper. We present an electromagnetic formulation of scattering aperture elements' PD. In the formulation, the PD brings an additional degree of freedom in the generation of the measurement matrix, given the apertures being illuminated with varying polarizations. This new degree of freedom enables a potential of reducing the coherences. Two complementary electric-field-coupled (cELC) scattering apertures, which differentiate in the polarizations of elements, are fabricated for validation. A set of comparisons yielded by the near-field scanning data of these apertures shows that the PD effectively reduces coherences and improves reconstruction performance.
"Coherence Reduction of the Measurement Matrix in Microwave Computational Imaging by Introducing Polarization Diversity," Progress In Electromagnetics Research C,
Vol. 99, 1-14, 2020. doi:10.2528/PIERC19100707
1. Mait, J. N., G. W. Euliss, and R. A. Athale, "Computational imaging," Advances in Optics and Photonics, Vol. 10, 409-483, 2018. doi:10.1364/AOP.10.000409
2. Yurduseven, O., T. Fromenteze, K. Cooper, G. Chattopadhyay, and D. R. Smith, "From microwaves to submillimeter waves: Modern advances in computational imaging, radar, and future trends," Proceedings of Society of Photographic Instrumentation Engineers, Vol. 10917, San Francisco, United States, Feb. 2-7, 2019.
3. Guan, J. and W. Chen, "On the coherence relationship between measurement matrices and equivalent radiation sources in microwave computational imaging applications," Applied Sciences, Vol. 9, 1172, 2019. doi:10.3390/app9061172
4. Huang, K. and X. Zhao, Inverse Problems in Electromagnetic Fields and Its Applications, 1st Ed., Science Press, Beijing, China, 2005 (in Chinese).
5. Gureyev, T. E., D. M. Paganin, A. Kozlov, Ya. I. Nesterets, and H. M. Quiney, "Complementary aspects of spatial resolution and signal-to-noise ratio in computational imaging," Physical Review A, Vol. 97, 053819, 2018. doi:10.1103/PhysRevA.97.053819
6. Carin, L., D. Liu, and B. Guo, "Coherence, compressive sensing, and random sensor arrays," IEEE Antennas and Propagation Magazine, Vol. 53, 28-39, 2011. doi:10.1109/MAP.2011.6097283
7. Hunt, J., T. Driscoll, A. Mrozack, G. Lipworth, M. Reynolds, D. Brady, and D. R. Smith, "Metamaterial apertures for computational imaging," Science, Vol. 339, 310-313, 2013. doi:10.1126/science.1230054
8. Lipworth, G., A. Mrozack, J. Hunt, D. L. Marks, T. Driscoll, D. Brady, and D. R. Smith, "Metamaterial apertures for coherent computational imaging on the physical layer," Journal of Optical Society of America A, Vol. 30, 1603-1612, 2013. doi:10.1364/JOSAA.30.001603
9. Hunt, J., J. Gollub, T. Driscoll, G. Lipworth, A. Mrozack, M. S. Reynolds, D. J. Brady, and D. R. Smith, "Metamaterial microwave holographic imaging system," Journal of Optical Society of America A, Vol. 31, 2109-2119, 2014. doi:10.1364/JOSAA.31.002109
10. Fromenteze, T., O. Yurduseven, M. F. Imani, J. Gollub, C. Decroze, D. Carsenat, and D. R. Smith, "Computational imaging using a mode-mixing cavity at microwave frequencies," Applied Physics Letters, Vol. 106, 194104, 2015. doi:10.1063/1.4921081
11. Imani, M. F., T. Sleasman, J. N. Gollub, and D. R. Smith, "Analytical modeling of printed metasurface cavities for computational imaging," Journal of Applied Physics, Vol. 120, 144903, 2016. doi:10.1063/1.4964336
12. Marks, D. L., J. Gollub, and D. R. Smith, "Spatially resolving antenna arrays using frequency diversity," Journal of Optical Society of America A, Vol. 33, 899-912, 2016. doi:10.1364/JOSAA.33.000899
13. Sleasman, T., M. F. Imani, J. N. Gollub, and D. R. Smith, "Dynamic metamaterial aperture for microwave imaging," Applied Physics Letters, Vol. 107, 204104, 2015. doi:10.1063/1.4935941
14. Wu, Z., L. Zhang, H. Liu, and N. Kou, "Enhancing microwave metamaterial aperture radar imaging performance with rotation synthesis," IEEE Sensors Journal, Vol. 16, 8035-8043, 2016. doi:10.1109/JSEN.2016.2609200
15. Yoya, A. C. T., B. Fuchs, C. Leconte, and M. Davy, "A reconfigurable chaotic cavity with fluorescent lamps for microwave computational imaging," Progress In Electromagnetics Research, Vol. 165, 1-12, 2019. doi:10.2528/PIER19011602
16. Zhu, S., X. Dong, Y. He, M. Zhao, G. Dong, X. Chen, and d A. Zhang, "Frequency-polarization-diverse aperture for coincidence imaging," IEEE Microwave and Wireless Components Letters, Vol. 28, 82-84, 2018. doi:10.1109/LMWC.2017.2769448
17. Poon, A. and D. Tse, "Polarization degrees of freedom," Proceedings of 2008 IEEE International Symposium on Information Theory, 1587-1591, Toronto, Canada, Jul. 6-11, 2008.
18. Chew, W.-C., Waves and Fields in Inhomogeneous Media, 1st Ed., IEEE Press, New York, United States, 1995.
19. Van Den Berg, P. M. and R. E. Kleinman, "A contrast source inversion method," Inverse Problems, Vol. 13, 1607-1620, 1997. doi:10.1088/0266-5611/13/6/013
20. Sleasman, T., M. Boyarsky, M. F. Imani, J. N. Gollub, and D. R. Smith, "Design considerations for a dynamic metamaterial aperture for computational imaging at microwave frequencies," Journal of Optical Society of America B, Vol. 33, 1098-1111, 2016. doi:10.1364/JOSAB.33.001098
21. Hori, M., "Inverse analysis method using spectral decomposition of Green’s function," Geophysical Journal International, Vol. 147, 77-87, 2001.
22. Kastner, R., "On the singularity of the full spectral Green’s dyad," IEEE Transactions on Antennas and Propagation, Vol. 35, 1303-1305, 1987. doi:10.1109/TAP.1987.1144016
23. Pellat-Finet, P., "Fresnel diffraction and the fractional-order Fourier transform," Optics Letters, Vol. 19, 1388-1390, 1994. doi:10.1364/OL.19.001388
24. Alieva Vicente Lopez, T., F. Agullo-Lopez, and L. B. Almeida, "The fractional Fourier transform in optical propagation problems," Journal of Modern Optics, Vol. 41, 1037-1044, 1994. doi:10.1080/09500349414550971
25. Ledger, P. D. and W. R. Bill Lionheart, "Understanding the magnetic polarizability tensor," IEEE Transactions on Magnetics, Vol. 52, 1-16, 2016. doi:10.1109/TMAG.2015.2507169
26. Duarte-Carvajalino, J. M. and G. Sapiro, "Learning to sense sparse signals: Simultaneous sensing matrix and sparsifying dictionary optimization," IEEE Transactions on Image Processing, Vol. 18, 1395-1408, 2009. doi:10.1109/TIP.2009.2022459
27. Bioucas-Dias, J. M. and M. A. T. Figueiredo, "A new TwIST: Two-step iterative shrinkage/thresholding algorithms for image restoration," IEEE Transactions on Image Processing, Vol. 16, 2992-3004, 2007. doi:10.1109/TIP.2007.909319