This paper proposes a hybrid electromagnetic field inverse scattering imaging method based on the advantages of the qualitative and quantitative imaging methods，and it is applied to rebuilding the space distribution information of electric parameters for multi objects. First, the prior knowledge of the Region Of Interesting (ROI) of target, object shape and target number is reconstructed by using Direct Sampling Method (DSM). Then, the geometry information of the objects and the space iteratively corrected distribution information of electric parameters is reconstructed by Subspace-based Optimization quantitative Method(SOM). The experimental result for the scattering field data of Fresnel laboratory shows that the imaging accuracy of this method is comparable to SOM. More over, the proposed technique greatly reduces the computational complexity and improves the convergence speed.
SHAH P, KHANKHOJE U, and MOGHADDAM M. Inverse scattering using a joint L1-L2 based regularization[J]. IEEE Transactions on Antennas and Propagation, 2016, 64(4): 1373-1384. doi: 10.1109/TAP.2016.2529641.
[2]
RABBANI M, TAWAKONI A, and DEHMOLLAIAN M. A hybrid quantitative method for inverse scattering of multiple dielectric objects[J]. IEEE Transactions on Antennas and Propagation, 2016, 64(3): 977-987. doi: 10.1109/TAP.2016. 2515124.
[3]
CHEN X. Subspace-based optimization method for solving inverse-scattering problems[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(1): 42-49. doi: 10.1109/TGRS.2009.2025122.
[4]
CUI Tiejun, AYDINER A, CHEN Siyuan, et al. Inverse scattering of two-dimensional dielectric objects buried in a lossy earth using the distorted Born iterative method[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(2): 339-346. doi: 10.1109/36.905242.
[5]
DONATO L D, BEVACQUA M T, CROCK L, et al. Inverse scattering via virtual experiments and contrast source regularization[J]. IEEE Transactions on Antennas and Propagation, 2015, 63(4): 1669-1677. doi: 10.1109/TAP.2015. 2392124.
[6]
CAPONE F and DARRIGRAND E. The linear sampling method for the inverse electromagnetic scattering problem for screens[C]. Society for Industrial and Applied Mathematics, 2010: 645-646.
[7]
ITO K, JIN B, and ZHOU J. A direct sampling method to an inverse medium scattering problem[J]. Inverse Problems, 2012, 28(2): 25003-25013. doi: 10.1088/0266-5611/28/2/ 025003.
[8]
XU K, ZHONG Y, SONG R, et al. Multiplicative-regularized FFT twofold subspace-based optimization method for inverse scattering problems[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(2): 841-850. doi: 10.1109/ TGRS.2014.2329032.
[9]
BRIGNONE M, BOZZA G, RANDAZZO A, et al. A hybrid approach to 3D microwave imaging by using linear sampling and ACO[J]. IEEE Transactions on Antennas and Propagation, 2008, 56(10): 3224-3232. doi: 10.1109/TAP. 2008.929504.
[10]
DORN O and ELSEVIER D. Level set methods for inverse scattering[J]. Inverse Problems, 2006, 22(22): R67-R131. doi: 10.1088/0266-5611/22/4/R01.
[11]
YE X, POLE L, OLIVIER G, et al. Multi-resolution subspace-based optimization method for solving three- dimensional inverse scattering problems[J]. Journal of the Optical Society of America A, 2015, 32(11): 2218-2226. doi: 10.1364/JOSAA.32.002218.
[12]
SORIMACHI M and NISHIMURA S. Guest editors’ introduction: testing inversion algorithms against experimental data: inhomogeneous targets[J]. Inverse Problems, 2005, 21(6): S1-S3. doi: 10.1016/0168-0102(85) 90273.
XIAO Zhitao, SHI Wenjing, GENG Lei, et al. Symmetry detection based on phase information and principal component analysis[J]. Journal of Electronics & Information Technology, 2014, 36(9): 2041-2046. doi: 10.3724/SP.J.1146. 2013.01598.
