The Community for Technology Leaders
RSS Icon
Issue No.06 - June (2013 vol.12)
pp: 1225-1235
M. R. Basheer , Depts. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
S. Jagannathan , Depts. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
This paper presents a novel localization scheme in the 3D wireless domain that employs cross correlation in backscattered signal power from a cluster of radio frequency identification (RFID) tags to estimate their location. Spatially co-located RFID tags, energized by a common tag reader, exhibit correlation in their received signal strength indicator (RSSI) values. Hence, for a cluster of RFID tags, the posterior distribution of their unknown radial separation is derived as a function of the measured RSSI correlations between them. The global maxima of this posterior distribution represent the actual radial separation between the RFID tags. The radial separations are then utilized to obtain location estimates of the tags. However, due to the nonconvex nature of the posterior distribution, deterministic optimization methods that are used to solve true radial separations between tags provide inaccurate results due to local maxima, unless the initial radial separation estimates are within the region of attraction of its global maximum. The proposed RFID localization algorithm called LOCalization Using Stochastic Tunneling (LOCUST) utilizes constrained simulated annealing with tunneling transformation to solve this nonconvex posterior distribution. The tunneling transformation allows the optimization search operation to circumvent or “tunnel” through ill-shaped regions in the posterior distribution resulting in faster convergence to the global maximum. Finally, simulation results of our localization method are presented to demonstrate the theoretical conclusions.
Correlation, Joints, Vectors, Fading, Passive RFID tags, stochastic tunneling, Antenna correlation, Rayleigh channel, fading, spatial diversity, maximum a posteriori, Markov Chain Monte Carlo, composite likelihood, multidimensional scaling
M. R. Basheer, S. Jagannathan, "Localization of RFID Tags Using Stochastic Tunneling", IEEE Transactions on Mobile Computing, vol.12, no. 6, pp. 1225-1235, June 2013, doi:10.1109/TMC.2012.80
[1] R. Want, "An Introduction to RFID Technology," IEEE Pervasive Computing, vol. 5, no. 1, pp. 25-33, Jan.-Mar. 2006.
[2] P.V. Nikitin and K.V.S. Rao, "Theory and Measurement of Backscattering from RFID Tags," IEEE Antennas and Propagation Magazine, vol. 48, no. 6, pp. 212-218, Dec. 2006.
[3] C. Hillbrand and S. Robert, "Shipment Localization Kit: An Automated Approach for Tracking and Tracing General Cargo," Proc. Int'l Conf. Management of Mobile Business, vol. 46, pp. 9-11, July 2007.
[4] P.V. Nikitin, R. Martinez, S. Ramamurthy, H. Leland, G. Spiess, and K.V.S Rao, "Phase Based Spatial Identification of UHF RFID Tags," Proc. IEEE Int'l Conf. RFID, pp. 102-109, Apr. 2010.
[5] M. Kim and N. Chong, "Direction Sensing RFID Reader for Mobile Robot Navigation," IEEE Trans. Automation Science and Eng., vol. 6, no. 1, pp. 44-54, Jan. 2009.
[6] Y. Park, J.W. Lee, and S.W. Kim, "Improving Position Estimation on RFID Tag Floor Localization Using RFID Reader Transmission Power Control," Proc. IEEE Int'l Conf. Robotics and Biomimetics, pp. 1716-1721, Feb. 2009.
[7] M.R. Basheer and S. Jagannathan, "R-Factor: A New Parameter to Enhance Location Accuracy in RSSI Based Real-Time Location Systems," Proc. IEEE Sixth Ann. Comm. Soc. Conf. Sensor, Mesh and Ad Hoc Comm. and Networks, pp. 1-9, June 2009.
[8] X. Ji and H. Zha, "Sensor Positioning in Wireless Ad-Hoc Sensor Networks Using Multidimensional Scaling," Proc. IEEE 23rd Ann. Joint Conf. Comp. and Comm. Soc., vol. 4, pp. 2652-2661, Mar. 2004.
[9] J.A. Costa, N. Patwari, and A.O. Hero, "Distributed Weighted-Multidimensional Scaling for Node Localization in Sensor Networks," ACM Trans. Sensor Networks, vol. 2, no. 1, pp. 39-64, Feb. 2006.
[10] Y. Shang, W. Ruml, Y. Zhang, and M.P. Fromherz, "Localization from Mere Connectivity," Proc. Fourth ACM Int'l Symp. Mobile Ad Hoc Networking & Computing, pp. 201-212, June 2003.
[11] N. Patwari and A.O. Hero, "Manifold Learning Algorithms for Localization in Wireless Sensor Networks," Proc. IEEE Int'l Conf. Acoustics, Speech and Signal Processing, vol. 3, pp. 857-860, May 2004.
[12] C. Wang, J. Chen, Y. Sun, and X. Shen, "Wireless Sensor Networks Localization with Isomap," Proc. IEEE Int'l Conf. Comm., June 2009.
[13] J.N. Ash and R.L Moses, "On Optimal Anchor Node Placement in Sensor Localization by Optimization of Subspace Principal Angles," Proc. IEEE Int'l Conf. Acoustics, Speech and Signal Processing, pp. 2289-2292, Apr. 2008.
[14] K.V. Mardia and P.E. Jupp, Directional Statistics. John Wiley and Sons, 2000.
[15] M. Abramowitz and I. Stegun, Handbook of Mathematical Functions. Dover, 1968.
[16] C. Varin and P. Vidoni, "Pairwise Likelihood Inference for General State Space Models," Econometrics Rev., vol. 28, nos. 1/2, pp. 170-185, Sept. 2009.
[17] C. Varin, N. Reid, and D. Firth, "An Overview on Composite Likelihood Methods," Statistica Sinica, vol. 21, pp. 5-42, 2011.
[18] G.L. Stuber, Principles of Mobile Communication. Kluwer Academic, 1996.
[19] F. Downton, "Bivariate Exponential Distributions in Reliability Theory," J. Royal Statistical Soc., vol. 32, pp. 408-417, 1970.
[20] S. Nadarajah and S. Kotz, "Sums, Products, and Ratios for Downton's Bivariate Exponential Distribution," Stochastic Environmental Research Risk Assessment, vol. 20, no. 3, pp. 164-170, 2006.
[21] R. Fisher, "The Truncated Normal Distribution," British Assoc. for the Advancement of Science, Math. Tables, vol. 5, pp. 33-34, 1931.
[22] A. Ramachandran and S. Jagannathan, "Spatial Diversity in Signal Strength Based WLAN Location Determination Systems," Proc. IEEE 32nd Conf. Local Comp. Networks, pp. 10-17, Oct. 2007.
[23] N.M. Laurendeau, Statistical Thermodynamics: Fundamentals and Applications. Cambridge Univ., 2005.
[24] S.J. Wu, D.H. Chen, and S.T. Chen, "Bayesian Inference for Rayleigh Distribution under Progressive Censored Sample," Applied Stochastic Models in Business and Industry, vol. 22, no. 3, pp. 269-279, May 2006.
[25] A.E. Gelfand and A.F.M Smith, "Sampling-Based Approaches to Calculating Marginal Densities," J. Am. Statistical Assoc., vol. 85, no. 410, pp. 398-409, June 1990.
[26] S. Banerjee, T.G. Griffin, and M. Pias, "The Interdomain Connectivity of PlanetLab Nodes," Proc. Passive and Active Measurement Workshop, 2004.
[27] R. Seidel, "The Upper Bound Theorem for Polytopes: An Easy Proof of Its Asymptotic Version," Computational Geometry, vol. 5, no. 2, pp. 115-116, Sept. 1995.
[28] B. Gidas, "Non Stationary Markov Chains and Convergence of Simulated Annealing Algorithms," J. Statistical Physics, vol. 39, pp. 73-131, Apr. 1985.
[29] B.W. Wah, Y. Chen, and T. Wang, "Simulated Annealing with Asymptotic Convergence for Nonlinear Constrained Optimization," J. Global Optimization, vol. 39, no. 1, pp. 1-37, Sept. 2007.
[30] W. Wenzel and K. Hamacher, "Stochastic Tunneling Approach for Global Minimization of Complex Potential Energy Landscapes," Am. Physical Soc., vol. 82, no. 5, pp. 3003-3007, Apr. 1999.
[31] K.S. Arun, T.S. Huang, and S.D. Bolstein, "Least Square Fitting of Two 3-D Point Sets," IEEE Trans. Pattern Analysis Machine Intelligence, vol. 9, no. 5, pp. 698-700, Sept. 1987.
21 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool