The Linear Sampling Method as a Tool for “Blind” Field Intensity Shaping

Arbitrary shaping the field intensity is a challenging problem relevant in many applications. To date, procedures addressing such a challenging problem have been developed assuming a full knowledge of both the scenario and the target within embedded. However, this is not the case in many applications where the investigated scenario is only approximately known and/or modeled on the basis of some auxiliary imaging methods. In this article, we propose a novel adaptive procedure able to shape the field intensity in an unknown (or partially unknown) scenario without the need of a quantitative scenario retrieval. The approach takes advantage from the linear sampling method, which belongs to the class of qualitative imaging methods, in order to focus the field intensity with respect to different control points belonging to the target. Then, the desired spatial field intensity shaping is obtained by recombining the results from such single-focusing problems and by exploiting an additional degree of freedom, which is represented by phase shifts of the field in the considered control points. A preliminary numerical validation and assessment are given for in-homogeneous and lossy unknown 2-D scenarios.

[1]  Álvaro Marco,et al.  Location-based services for elderly and disabled people , 2008, Comput. Commun..

[2]  Francesco G. Della Corte,et al.  An autonomous and energy efficient Smart Sensor Platform , 2014, IEEE SENSORS 2014 Proceedings.

[3]  D. Colton,et al.  The linear sampling method in inverse electromagnetic scattering theory , 2003 .

[4]  Cyril Leung,et al.  RF energy harvesting in DF relay networks in the presence of an interfering signal , 2016, 2016 IEEE International Conference on Communications (ICC).

[5]  Min Zhu,et al.  Generating Microwave Spatial Fields With Arbitrary Patterns , 2016, IEEE Antennas and Wireless Propagation Letters.

[6]  Ahmed E. Kamal,et al.  Energy Harvesting in Heterogeneous Networks with Hybrid Powered Communication Systems , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[7]  Themistoklis Charalambous,et al.  Optimal Radio Frequency Energy Harvesting With Limited Energy Arrival Knowledge , 2015, IEEE Journal on Selected Areas in Communications.

[8]  M. Paulides,et al.  Status quo and directions in deep head and neck hyperthermia , 2016, Radiation Oncology.

[9]  T. Isernia,et al.  An Improved Simple Method for Imaging the Shape of Complex Targets , 2013, IEEE Transactions on Antennas and Propagation.

[10]  Fioralba Cakoni,et al.  The linear sampling method for cracks , 2003 .

[11]  Lorenzo Crocco,et al.  An Algebraic Solution Method for Nonlinear Inverse Scattering , 2015, IEEE Transactions on Antennas and Propagation.

[12]  Ugur Alkasi,et al.  Experimental Assessment of Linear Sampling and Factorization Methods for Microwave Imaging of Concealed Targets , 2015 .

[13]  Yoshinobu Ebisawa A pilot study on ultrasonic sensor-based measurement of head movement , 2002, IEEE Trans. Instrum. Meas..

[14]  G C van Rhoon,et al.  The potential of constrained SAR focusing for hyperthermia treatment planning: analysis for the head & neck region , 2018, Physics in medicine and biology.

[15]  R. Kress,et al.  Inverse Acoustic and Electromagnetic Scattering Theory , 1992 .

[16]  Radu Ionescu,et al.  Three dimensional ultrasound gestural interface , 2009, 2009 IEEE International Ultrasonics Symposium.

[17]  Gennaro G. Bellizzi,et al.  Three-Dimensional Field Intensity Shaping: The Scalar Case , 2018, IEEE Antennas and Wireless Propagation Letters.

[18]  Lorenzo Crocco,et al.  AN ADAPTIVE METHOD TO FOCUSING IN AN UNKNOWN SCENARIO , 2012 .

[19]  T. Isernia,et al.  On Simple Methods for Shape Reconstruction of Unknown Scatterers , 2007, IEEE Transactions on Antennas and Propagation.

[20]  Mario Bertero,et al.  Introduction to Inverse Problems in Imaging , 1998 .

[21]  Gregory Cohen,et al.  EMNIST: an extension of MNIST to handwritten letters , 2017, CVPR 2017.

[22]  G. Franceschetti,et al.  On the degrees of freedom of scattered fields , 1989 .

[23]  Bernhard E. Boser,et al.  12.1 3D ultrasonic gesture recognition , 2014, 2014 IEEE International Solid-State Circuits Conference Digest of Technical Papers (ISSCC).

[24]  Paolo Nepa,et al.  Design of a Near-Field Focused Reflectarray Antenna for 2.4 GHz RFID Reader Applications , 2011, IEEE Transactions on Antennas and Propagation.

[25]  M. Fink,et al.  Time reversal of ultrasonic fields. I. Basic principles , 1992, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[26]  P. Potier,et al.  3D near-field shaping of a focused aperture , 2016, 2016 10th European Conference on Antennas and Propagation (EuCAP).

[27]  Tommaso Isernia,et al.  Electromagnetic inverse scattering: Retrievable information and measurement strategies , 1997 .

[28]  Tom Chau,et al.  A Review of Indoor Localization Technologies: towards Navigational Assistance for Topographical Disorientation , 2010 .

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

[30]  T Isernia,et al.  Improved quantitative microwave tomography by exploiting the physical meaning of the Linear Sampling Method , 2011, Proceedings of the 5th European Conference on Antennas and Propagation (EUCAP).

[31]  T. Isernia,et al.  The Linear Sampling Method as a Way to Quantitative Inverse Scattering , 2012, IEEE Transactions on Antennas and Propagation.

[32]  Antonio Iera,et al.  Performance assessment of an enhanced RFID sensor tag for long-run sensing applications , 2014, IEEE SENSORS 2014 Proceedings.