Vol. 14
Latest Volume
All Volumes
PIERL 123 [2025] PIERL 122 [2024] PIERL 121 [2024] PIERL 120 [2024] PIERL 119 [2024] PIERL 118 [2024] PIERL 117 [2024] PIERL 116 [2024] PIERL 115 [2024] PIERL 114 [2023] PIERL 113 [2023] PIERL 112 [2023] PIERL 111 [2023] PIERL 110 [2023] PIERL 109 [2023] PIERL 108 [2023] PIERL 107 [2022] PIERL 106 [2022] PIERL 105 [2022] PIERL 104 [2022] PIERL 103 [2022] PIERL 102 [2022] PIERL 101 [2021] PIERL 100 [2021] PIERL 99 [2021] PIERL 98 [2021] PIERL 97 [2021] PIERL 96 [2021] PIERL 95 [2021] PIERL 94 [2020] PIERL 93 [2020] PIERL 92 [2020] PIERL 91 [2020] PIERL 90 [2020] PIERL 89 [2020] PIERL 88 [2020] PIERL 87 [2019] PIERL 86 [2019] PIERL 85 [2019] PIERL 84 [2019] PIERL 83 [2019] PIERL 82 [2019] PIERL 81 [2019] PIERL 80 [2018] PIERL 79 [2018] PIERL 78 [2018] PIERL 77 [2018] PIERL 76 [2018] PIERL 75 [2018] PIERL 74 [2018] PIERL 73 [2018] PIERL 72 [2018] PIERL 71 [2017] PIERL 70 [2017] PIERL 69 [2017] PIERL 68 [2017] PIERL 67 [2017] PIERL 66 [2017] PIERL 65 [2017] PIERL 64 [2016] PIERL 63 [2016] PIERL 62 [2016] PIERL 61 [2016] PIERL 60 [2016] PIERL 59 [2016] PIERL 58 [2016] PIERL 57 [2015] PIERL 56 [2015] PIERL 55 [2015] PIERL 54 [2015] PIERL 53 [2015] PIERL 52 [2015] PIERL 51 [2015] PIERL 50 [2014] PIERL 49 [2014] PIERL 48 [2014] PIERL 47 [2014] PIERL 46 [2014] PIERL 45 [2014] PIERL 44 [2014] PIERL 43 [2013] PIERL 42 [2013] PIERL 41 [2013] PIERL 40 [2013] PIERL 39 [2013] PIERL 38 [2013] PIERL 37 [2013] PIERL 36 [2013] PIERL 35 [2012] PIERL 34 [2012] PIERL 33 [2012] PIERL 32 [2012] PIERL 31 [2012] PIERL 30 [2012] PIERL 29 [2012] PIERL 28 [2012] PIERL 27 [2011] PIERL 26 [2011] PIERL 25 [2011] PIERL 24 [2011] PIERL 23 [2011] PIERL 22 [2011] PIERL 21 [2011] PIERL 20 [2011] PIERL 19 [2010] PIERL 18 [2010] PIERL 17 [2010] PIERL 16 [2010] PIERL 15 [2010] PIERL 14 [2010] PIERL 13 [2010] PIERL 12 [2009] PIERL 11 [2009] PIERL 10 [2009] PIERL 9 [2009] PIERL 8 [2009] PIERL 7 [2009] PIERL 6 [2009] PIERL 5 [2008] PIERL 4 [2008] PIERL 3 [2008] PIERL 2 [2008] PIERL 1 [2008]
2010-05-09
A Novel Linear EM Reconstruction Algorithm with Phaseless Data
By
Progress In Electromagnetics Research Letters, Vol. 14, 133-146, 2010
Abstract
This paper presents a fast and effective electromagnetic reconstruction algorithm with phaseless data under weak scattering conditions. The proposed algorithm is based on the phaseless data multiplicative regularized contrast sources inversion method (PD-MRCSI). We recast the weak scattering problem as an optimization problem in terms of the undetermined contrast and contrast sources. Using the conjugate gradient iterative method, the problem is solved by alternately updating the contrast sources and the contrast. Additionally, this method can combine with the PD-MRCSI method. Taking advantage of the properties of fast convergence of this algorithm and stable convergence of PD-MRCSI method, the combined technique makes image reconstructions more fast and effective. Although the method is derived from weak scattering situation, it is also useful for the case which weak scattering approximation is not satisfied. The synthetic numerical reconstruction results, as well as experimental reconstruction results, presented that the proposed method is a very fast and effective reconstruction algorithm.
Citation
Hu Zheng, Ming-Zhen Wang, Zhiqin Zhao, and Lianlin Li, "A Novel Linear EM Reconstruction Algorithm with Phaseless Data," Progress In Electromagnetics Research Letters, Vol. 14, 133-146, 2010.
doi:10.2528/PIERL10031306
References

1. Chew, W. C. and Y. M. Wang, "Reconstruction of two-dimensional permittivity distribution using the distorted Born iterative method," IEEE Trans. Med. Imaging., Vol. 9, 218-225, 1990.
doi:10.1109/42.56334

2. Zhang, Z. Q. and Q. H. Liu, "Two nonlinear inverse methods for electromagnetic induction measurements," IEEE Trans. Geosci. Remote Sens., Vol. 39, 1331-1339, 2001.
doi:10.1109/36.927456

3. 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

4. Abubakar, A., T. M. Habashy, and P. M. van den Berg, "Nonlinear inversion of multi-frequency microwave Fresnel data using the multiplicative regularized contrast source inversion," Progress In Electromagnetics Research, Vol. 62, 193-201, 2006.
doi:10.2528/PIER06042205

5. Abubakar, A., P. M. van den Berg, and S. Y. Semenov, "A robust iterative method for born inversion," IEEE Trans. Geosci. Remote Sens., Vol. 42, 342-354, 2004.
doi:10.1109/TGRS.2003.821062

6. Abubakar, A., P. M. van den Berg, and S. Y. Semenov, "Two- and three-dimensional algorithms for microwave imaging and inverse scattering ," Journal of Electromagnetic Waves and Applications, Vol. 17, No. 2, 209-231, 2003.
doi:10.1163/156939303322235798

7. Crocco, L. and T. Isernia, "Inverse scattering with real data: Detecting and imaging homogeneous dielectric objects," Inverse Problems, Vol. 17, 1573-1583, 2001.
doi:10.1088/0266-5611/17/6/302

8. Torresverdin, C. and T. M. Habashy, "Rapid 2.5-dimensional forward modeling and inversion via a new nonlinear scattering approximation," Radio Sci., Vol. 29, 1051-1079, 1994.
doi:10.1029/94RS00974

9. Zhdanov, M. and G. Hursan, "3D electromagnetic inversion based on quasi-analytical approximation," Inverse Problems, Vol. 16, 1297-1322, 2000.
doi:10.1088/0266-5611/16/5/311

10. Guo, B., Y. Wang, J. Li, P. Stoica, and R. Wu, "Microwave imaging via adaptive beamforming methods for breast cancer detection," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 1, 53-63, 2006.
doi:10.1163/156939306775777350

11. Karanasiou, I. S., N. K. Uzunoglu, and A. Garetsos, "Electro-magnetic analysis of a non-invasive 3D passive microwave imaging system," Journal of Electromagnetic Waves and Applications, Vol. 18, No. 3, 379-380, 2004.
doi:10.1163/156939304323085793

12. Franceschini, G., M. Donelli, D. Franceschini, M. Benedetti, P. Rocca, and A. Massa, "Microwave imaging from amplitude-only data-advantages and open problems of a two-step multi-resolution strategy ," Progress In Electromagnetics Research, Vol. 83, 397-412, 2008.
doi:10.2528/PIER08062904

13. Zhou, H., T. Takenaka, J. Johnson, and T. Tanaka, "A breast imaging model using microwaves and a time domain three dimensional reconstruction method," Progress In Electromagnetics Research, Vol. 93, 57-70, 2009.
doi:10.2528/PIER09033001

14. Dai, S. Y., C. Zhang, and Z.-S. Wu, "Electromagnetic scattering of objects above ground using MRTD/FDTD hybrid method," Journal of Electromagnetic Waves and Applications, Vol. 23, No. 16, 2187-2196, 2006.
doi:10.1163/156939309790109306

15. Caorsi, S., A. Massa, M. Pastorino, and A. Randazzo, "Electromagnetic detection of dielectric scatterers using phaseless synthetic and real data and the memetic algorithm," IEEE Trans. Geosci. Remote Sens., Vol. 41, 2745-2753, 2003.
doi:10.1109/TGRS.2003.815676

16. Litman, A. and K. Belkebir, "Two-dimensional inverse profiling problem using phaseless data," J. Opt. Soc. Am. A, Vol. 23, 2737-2746, 2006.
doi:10.1364/JOSAA.23.002737

17. Crocco, L., M. D'Urso, and T. Isernia, "Faithful non-linear imaging from only-amplitude measurements of incident and total fields," Optics Express, Vol. 15, 3804-3815, 2007.
doi:10.1364/OE.15.003804

18. D'Urso, M., K. Belkebir, L. Crocco, T. Isernia, and A. Litman, "Phaseless imaging with experimental data: Facts and challenges," J. Opt. Soc. Am. A, Vol. 25, 271-281, 2008.
doi:10.1364/JOSAA.25.000271

19. Zheng, H., L. Li, and F. Li, "A multi-frequency MRCSI algorithm with phaseless data," Inverse Problems, Vol. 25, 1-13, 2009.

20. Li, L. L., H. Zheng, and F. Li, "Two-dimensional contrast source inversion method with phaseless data: TM case," IEEE Trans. Geosci. Remote Sens., Vol. 47, 1719-1736, 2009.
doi:10.1109/TGRS.2008.2006360

21. Belkebir, K. and M. Saillard, "Special section: Test inversion algorithms against experimental data," Inverse Problems, Vol. 17, 1565-1571, 2001.
doi:10.1088/0266-5611/17/6/301