Short-Range Wireless Localization Based on Meta-Aperture Assisted Compressed Sensing

Wireless localization has become a hot topic in the area of microwave engineering. In this paper, we propose a new approach for short-range wireless localization based on meta-aperture and compressed sensing (CS). Utilizing the plasmonic dispersion of a magnetically uniaxial metamaterial, a pushpin-shaped autocorrelation characteristic of the localization system can be obtained to ensure high localization precision. Compared with existing realizations based on traveling wave excited, randomly arranged subwavelength resonant elements, our method uses a homogeneous aperture for the generation of randomized illumination. Based on the CS, localization can be obtained with much less data and much faster data processing than conventional methods. Simulation and experimental investigation are conducted, and the results demonstrate the effectiveness of the proposed approach. With the simple implementation for fast localization, our method has promising potential in practical applications.

[1]  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.

[2]  Joachim Ender A brief review of compressive sensing applied to radar , 2013, 2013 14th International Radar Symposium (IRS).

[3]  Joel A. Tropp,et al.  Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.

[4]  Thomas Strohmer,et al.  Compressed sensing radar , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

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

[6]  A. Stelzer,et al.  A 77-GHz Cooperative Radar System Based on Multi-Channel FMCW Stations for Local Positioning Applications , 2013, IEEE Transactions on Microwave Theory and Techniques.

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

[8]  Wing-Kin Ma,et al.  Least squares algorithms for time-of-arrival-based mobile location , 2004, IEEE Transactions on Signal Processing.

[9]  Justin K. Romberg,et al.  Compressive Sensing by Random Convolution , 2009, SIAM J. Imaging Sci..

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

[11]  T. Engin Tuncer,et al.  Classical and Modern Direction-of-Arrival Estimation , 2009 .

[12]  P. Hudec,et al.  Microwave system for the detection and localization of mobile phones in large buildings , 2005, IEEE Transactions on Microwave Theory and Techniques.

[13]  Yaakov Tsaig,et al.  Extensions of compressed sensing , 2006, Signal Process..

[14]  Azzedine Boukerche,et al.  Localization systems for wireless sensor networks , 2007, IEEE wireless communications.

[15]  M.R. Mahfouz,et al.  Real-Time Noncoherent UWB Positioning Radar With Millimeter Range Accuracy: Theory and Experiment , 2010, IEEE Transactions on Microwave Theory and Techniques.

[16]  T. Sanpechuda,et al.  A review of RFID localization: Applications and techniques , 2008, 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[17]  N. Currie Radar reflectivity measurement: Techniques and applications , 1989 .

[18]  Richard P. Martin,et al.  The limits of localization using signal strength: a comparative study , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[19]  Martin Vossiek,et al.  Wireless local positioning , 2003 .

[20]  Arthur A. Oliner,et al.  Phased array antennas , 1972 .

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

[22]  Robert C. Hilborn,et al.  Chaos and Nonlinear Dynamics , 2000 .

[23]  Joachim H. G. Ender,et al.  On compressive sensing applied to radar , 2010, Signal Process..

[24]  Experimental characterization of the dispersive behavior in a uniaxial metamaterial around plasma frequency. , 2010, Optics express.

[25]  Nemai C. Karmakar,et al.  Chipless RFID Tag Localization , 2013, IEEE Transactions on Microwave Theory and Techniques.

[26]  Rosdiadee Nordin,et al.  Recent Advances in Wireless Indoor Localization Techniques and System , 2013, J. Comput. Networks Commun..

[27]  A. Benlarbi-Delai,et al.  Short-range two-dimension positioning by microwave cellular telemetry , 1994 .

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

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

[30]  T. Jiang,et al.  Rainbow-like radiation from an omni-directional source placed in a uniaxial metamaterial slab. , 2009, Optics express.

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

[32]  R. Weigel,et al.  A Reconfigurable MIMO System for High-Precision FMCW Local Positioning , 2011, IEEE Transactions on Microwave Theory and Techniques.

[33]  A.H. Sayed,et al.  Network-based wireless location: challenges faced in developing techniques for accurate wireless location information , 2005, IEEE Signal Processing Magazine.

[34]  R. Baraniuk,et al.  Compressive Radar Imaging , 2007, 2007 IEEE Radar Conference.

[35]  Michael R. Souryal,et al.  RFID-based localization and tracking technologies , 2011, IEEE Wireless Communications.

[36]  James D. Taylor,et al.  Ultrawideband Radar: Applications and Design , 2012 .

[37]  Moe Z. Win,et al.  Cooperative Localization in Wireless Networks , 2009, Proceedings of the IEEE.

[38]  P. Lacomme,et al.  Synthetic Aperture Radar , 2001 .

[39]  Richard G. Baraniuk,et al.  Compressive Sensing , 2008, Computer Vision, A Reference Guide.