Microwave Imaging Customized on Demand Under Random Field Illumination

Recently, microwave imaging under random field illuminations has attracted many interests. This paper theoretically analyzes and experimentally implements a qualitative microwave radar imaging system suitable for 2-D object. It can be customized on the demands of the desired object size and imaging resolution. Based on random illuminations generated by a minimum number of antenna elements, an analytical equation can be used to reconstruct the image of the object in near real time. The simple-structured and cost-effective imaging system can be implemented in microwave, millimeter-wave, and even sub-THz frequency bands, having promising potentials for various microwave imaging applications.

[1]  A. Massa,et al.  A Numerical Assessment of the Reconstruction Effectiveness of the Integrated GA-Based Multicrack Strategy , 2007, IEEE Antennas and Wireless Propagation Letters.

[2]  David R. Smith,et al.  Dynamic metamaterial aperture for microwave imaging , 2015 .

[3]  David R. Smith,et al.  Metamaterial Apertures for Computational Imaging , 2013, Science.

[4]  David R. Smith,et al.  Metamaterial microwave holographic imaging system. , 2014, Journal of the Optical Society of America. A, Optics, image science, and vision.

[5]  Xiang Wan,et al.  Transmission-Type 2-Bit Programmable Metasurface for Single-Sensor and Single-Frequency Microwave Imaging , 2016, Scientific Reports.

[6]  Xudong Chen,et al.  Computational Methods for Electromagnetic Inverse Scattering , 2018 .

[7]  Akira Ishimaru,et al.  Hard Wall Imaging of Objects Hidden by Non-Penetrating Obstacles Using Modified Time Reversal Technique , 2014, IEEE Transactions on Antennas and Propagation.

[8]  M. Tiebout,et al.  Advanced Microwave Imaging , 2012, IEEE Microwave Magazine.

[9]  L. Shafai,et al.  A Multiplicative Regularized Gauss–Newton Inversion for Shape and Location Reconstruction , 2011, IEEE Transactions on Antennas and Propagation.

[10]  M. Amin Through-the-Wall Radar Imaging , 2011 .

[11]  Vito Pascazio,et al.  A Multithreshold Iterative DBIM-Based Algorithm for the Imaging of Heterogeneous Breast Tissues , 2019, IEEE Transactions on Biomedical Engineering.

[12]  David R. Smith,et al.  Large Metasurface Aperture for Millimeter Wave Computational Imaging at the Human-Scale , 2017, Scientific Reports.

[13]  Yousuf Abo Rahama,et al.  Novel Microwave Tomography System Using a Phased-Array Antenna , 2018, IEEE Transactions on Microwave Theory and Techniques.

[14]  Michael Boyarsky,et al.  Design considerations for a dynamic metamaterial aperture for computational imaging at microwave frequencies , 2016 .

[15]  Changzhi Li,et al.  Wireless Hand Gesture Recognition Based on Continuous-Wave Doppler Radar Sensors , 2016, IEEE Transactions on Microwave Theory and Techniques.

[16]  Xudong Chen,et al.  Subspace-Based Distorted-Born Iterative Method for Solving Inverse Scattering Problems , 2017, IEEE Transactions on Antennas and Propagation.

[17]  Natalia K. Nikolova Introduction to Microwave Imaging: Contents , 2017 .

[18]  A. Abubakar,et al.  A contrast source inversion method in the wavelet domain , 2013 .

[19]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[20]  P. M. Berg,et al.  A contrast source inversion method , 1997 .

[21]  Amin M. Abbosh,et al.  A Rapid Medical Microwave Tomography Based on Partial Differential Equations , 2018, IEEE Transactions on Antennas and Propagation.

[22]  Sergey Kharkovsky,et al.  Dual-Laser Integrated Microwave Imaging System for Nondestructive Testing of Construction Materials and Structures , 2018, IEEE Transactions on Instrumentation and Measurement.

[23]  Thomas Fromenteze,et al.  Experimental Synthetic Aperture Radar With Dynamic Metasurfaces , 2017, IEEE Transactions on Antennas and Propagation.

[24]  Saudi Arabia,et al.  FPGA Design and Implementation of Matrix Multiplier Architectures for Image and Signal Processing Applications , 2010 .

[25]  Shu Hotta,et al.  Mathematical Physical Chemistry: Practical and Intuitive Methodology , 2018 .

[26]  Xudong Chen,et al.  Twofold subspace-based optimization method for solving inverse scattering problems , 2009 .

[27]  N. Nikolova Microwave Imaging for Breast Cancer , 2011, IEEE Microwave Magazine.

[28]  David R. Smith,et al.  Frequency-diverse microwave imaging using planar Mills-Cross cavity apertures. , 2016, Optics express.

[29]  Louis L. Scharf,et al.  The SVD and reduced rank signal processing , 1991, Signal Process..

[30]  Xudong Chen Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium , 2010 .

[31]  Matin Hashemi,et al.  A Matrix-Inversion Technique for FPGA-Based Real-Time EMT Simulation of Power Converters , 2019, IEEE Transactions on Industrial Electronics.

[32]  R.G. Baraniuk,et al.  Compressive Sensing [Lecture Notes] , 2007, IEEE Signal Processing Magazine.

[33]  Reza Zoughi,et al.  Fast 3-D Qualitative Method for Through-Wall Imaging and Structural Health Monitoring , 2015, IEEE Geoscience and Remote Sensing Letters.

[34]  David R. Smith,et al.  Printed Aperiodic Cavity for Computational and Microwave Imaging , 2016, IEEE Microwave and Wireless Components Letters.

[35]  Barry D. Van Veen,et al.  A 3-D Level Set Method for Microwave Breast Imaging , 2015, IEEE Transactions on Biomedical Engineering.

[36]  Weng Cho Chew,et al.  An iterative solution of the two‐dimensional electromagnetic inverse scattering problem , 1989, Int. J. Imaging Syst. Technol..

[37]  W. Chew,et al.  Reconstruction of two-dimensional permittivity distribution using the distorted Born iterative method. , 1990, IEEE transactions on medical imaging.

[38]  Alexander G. Yarovoy,et al.  A Linear Model for Microwave Imaging of Highly Conductive Scatterers , 2018, IEEE Transactions on Microwave Theory and Techniques.

[39]  D. Lesselier,et al.  A New Integral Equation Method to Solve Highly Nonlinear Inverse Scattering Problems , 2016, IEEE Transactions on Antennas and Propagation.

[40]  Roel Snieder The role of nonlinearity in inverse problems , 1998 .

[41]  David R. Smith,et al.  Metamaterial apertures for coherent computational imaging on the physical layer. , 2013, Journal of the Optical Society of America. A, Optics, image science, and vision.

[42]  Paolo Rocca,et al.  Compressive Sensing in Electromagnetics - A Review , 2015, IEEE Antennas and Propagation Magazine.