Interferometric Sounding Using a Metamaterial-Based Compressive Reflector Antenna

This paper describes a new coded interferometric system for sensing the physical temperature radiated from the Earth’s surface. The proposed system consists of a compressive reflector antenna (CRA) coated with metamaterial absorbers (MMAs). The CRA and the MMA are used to code the received electromagnetic (EM) field in space and in frequency, at the focal plane array. The MMA is modeled by an equivalent magnetodielectric medium having a definite thickness. A high-frequency method based on physical optics is used to build the sensing matrix of the system, and the inverse problem is solved using a Nesterov-based compressive sensing (CS) methodology. Numerical examples are carried out in order to reconstruct the physical temperature of the Earth’s surface. The performance of the proposed system is compared to that of the conventional interferometric system, GeoSTAR. Preliminary results show that the metamaterial-based CRA provides comparable performance to the GeoSTAR configuration with only half of the feeding elements while keeping the same physical aperture size for the two configurations.

[1]  David R. Smith,et al.  Resolution of the Frequency Diverse Metamaterial Aperture Imager , 2015 .

[2]  David R. Smith,et al.  Comprehensive simulation platform for a metamaterial imaging system. , 2015, Applied optics.

[3]  Shannon T. Brown,et al.  Prototyping GeoSTAR for the PATH Mission , 2007 .

[4]  Lawrence Carin,et al.  Bayesian Compressive Sensing , 2008, IEEE Transactions on Signal Processing.

[5]  Richard Obermeier,et al.  Model-Based Optimization of Compressive Antennas for High-Sensing-Capacity Applications , 2015, IEEE Antennas and Wireless Propagation Letters.

[6]  T. Nakajima,et al.  Negative refraction of inhomogeneous waves in lossy isotropic media , 2013, 1305.6393.

[7]  Cyril Decroze,et al.  Passive Coding Technique Applied to Synthetic Aperture Interferometric Radiometer , 2017, IEEE Geoscience and Remote Sensing Letters.

[8]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[9]  William Blackwell,et al.  A Single-Transceiver Compressive Reflector Antenna for High-Sensing-Capacity Imaging , 2016, IEEE Antennas and Wireless Propagation Letters.

[10]  Willie J Padilla,et al.  Metamaterial Electromagnetic Wave Absorbers , 2012, Advanced materials.

[11]  Willie J Padilla,et al.  Perfect metamaterial absorber. , 2008, Physical review letters.

[12]  Andrea Massa,et al.  Compressive Sensing Imaging of Non-Sparse 2D Scatterers by a Total-Variation Approach Within the Born Approximation , 2014, IEEE Transactions on Antennas and Propagation.

[13]  Adriano Camps,et al.  The visibility function in interferometric aperture synthesis radiometry , 2004, IEEE Transactions on Geoscience and Remote Sensing.

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

[15]  Ali Molaei,et al.  Active imaging using a metamaterial-based compressive reflector antenna , 2016, 2016 IEEE International Symposium on Antennas and Propagation (APSURSI).

[16]  Ali Molaei,et al.  Consensus-based imaging using ADMM for a Compressive Reflector Antenna , 2015, 2015 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting.

[17]  Bruno Picard,et al.  Comparison of regularized inversion methods in synthetic aperture imaging radiometry , 2005, IEEE Transactions on Geoscience and Remote Sensing.

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

[19]  H. M. Lee,et al.  Design of double negative metamaterial absorber cells using electromagnetic-field coupled resonators , 2011, Asia-Pacific Microwave Conference 2011.

[20]  P. Rocca,et al.  Directions-of-Arrival Estimation Through Bayesian Compressive Sensing Strategies , 2013, IEEE Transactions on Antennas and Propagation.

[21]  Y. Nesterov A method for solving the convex programming problem with convergence rate O(1/k^2) , 1983 .

[22]  Yurii Nesterov,et al.  Smooth minimization of non-smooth functions , 2005, Math. Program..

[23]  C Rappaport,et al.  Wave Scattering by Dielectric and Lossy Materials Using the Modified Equivalent Current Approximation (MECA) , 2010, IEEE Transactions on Antennas and Propagation.

[24]  E. Candès,et al.  Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.

[25]  Paolo Rocca,et al.  A Bayesian-Compressive-Sampling-Based Inversion for Imaging Sparse Scatterers , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[26]  T. Cui,et al.  Ultrathin multiband gigahertz metamaterial absorbers , 2011 .

[27]  Ali Molaei,et al.  Norm-1 Regularized Consensus-Based ADMM for Imaging With a Compressive Antenna , 2017, IEEE Antennas and Wireless Propagation Letters.

[28]  Ali Molaei,et al.  Interferometric sounding using a Compressive Reflector Antenna , 2016, 2016 10th European Conference on Antennas and Propagation (EuCAP).

[29]  P. Rocca,et al.  Reliable Diagnosis of Large Linear Arrays—A Bayesian Compressive Sensing Approach , 2012, IEEE Transactions on Antennas and Propagation.

[30]  Christopher Ruf,et al.  GeoSTAR - a microwave sounder for geostationary satellites , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[31]  Hyuk Park,et al.  PAU-SA: A Synthetic Aperture Interferometric Radiometer Test Bed for Potential Improvements in Future Missions , 2012, Sensors.

[32]  Juan Heredia Juesas,et al.  Single-transceiver compressive antenna for high-capacity sensing and imaging applications , 2015, 2015 9th European Conference on Antennas and Propagation (EuCAP).

[33]  A. Massa,et al.  Bayesian Compressive Sampling for Pattern Synthesis With Maximally Sparse Non-Uniform Linear Arrays , 2011, IEEE Transactions on Antennas and Propagation.

[34]  Christopher Ruf,et al.  Initial Results of the Geostationary Synthetic Thinned Array Radiometer (GeoSTAR) Demonstrator Instrument , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[35]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[36]  Emmanuel J. Candès,et al.  NESTA: A Fast and Accurate First-Order Method for Sparse Recovery , 2009, SIAM J. Imaging Sci..