Fingerprinting Localization in Wireless Networks Based on Received-Signal-Strength Measurements: A Case Study on WiMAX Networks

This paper considers the problem of fingerprinting localization in wireless networks based on received-signal-strength (RSS) observations. First, the performance of static localization using power maps (PMs) is improved with a new approach called the base-station-strict (BS-strict) methodology, which emphasizes the effect of BS identities in the classical fingerprinting. Second, dynamic motion models with and without road network information are used to further improve the accuracy via particle filters. The likelihood-calculation mechanism proposed for the particle filters is interpreted as a soft version (called BS-soft) of the BS-strict approach applied in the static case. The results of the proposed approaches are illustrated and compared with an example whose data were collected from a WiMAX network in a challenging urban area in the capitol city of Brussels, Belgium.

[1]  M. Pitt,et al.  Filtering via Simulation: Auxiliary Particle Filters , 1999 .

[2]  T. Singh,et al.  Efficient particle filtering for road-constrained target tracking , 2005, 2005 7th International Conference on Information Fusion.

[3]  F. Gustafsson,et al.  Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements , 2005, IEEE Signal Processing Magazine.

[4]  Branko Ristic,et al.  Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .

[5]  Krishna R. Pattipati,et al.  Ground target tracking with variable structure IMM estimator , 2000, IEEE Trans. Aerosp. Electron. Syst..

[6]  H. V. Trees.  Detection, Estimation, And Modulation Theory , 2001 .

[7]  A. Gualtierotti.  H. L. Van Trees, Detection, Estimation, and Modulation Theory, , 1976 .

[8]  Simon J. Godsill,et al.  On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..

[9]  G.B. Giannakis,et al.  Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks , 2005, IEEE Signal Processing Magazine.

[10]  Egils Sviestins,et al.  Multiple model algorithm based on particle filters for ground target tracking , 2007, 2007 10th International Conference on Information Fusion.

[11]  Lang Hong,et al.  Multirate interacting multiple model particle filter for terrain-based ground target tracking , 2006 .

[12]  Ling Liu,et al.  What Where Wi: An Analysis of Millions of Wi-Fi Access Points , 2007, 2007 IEEE International Conference on Portable Information Devices.

[13]  Timothy J. Robinson,et al.  Sequential Monte Carlo Methods in Practice , 2003 .

[14]  Weidong Wang,et al.  RSS-based Monte Carlo localisation for mobile sensor networks , 2008, IET Commun..

[15]  B. Anderson,et al.  Optimal Filtering , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[16]  David P. Kormann,et al.  802.11b access point mapping , 2003, CACM.

[17]  Ling Liu,et al.  Improving Wireless Positioning with Look-ahead Map-Matching , 2007, 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous).

[18]  O. Payne,et al.  An unscented particle filter for GMTI tracking , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[19]  Andreas F. Molisch,et al.  Localization via Ultra- Wideband Radios , 2005 .

[20]  Fredrik Gustafsson,et al.  POSSIBILITIES AND FUNDAMENTAL LIMITATIONS OF POSITIONING USING WIRELESS COMMUNICATION NETWORKS MEASUREMENTS , 2004 .

[21]  Peter J. Shea,et al.  Improved state estimation through use of roads in ground tracking , 2000, SPIE Defense + Commercial Sensing.

[22]  Simon J. Godsill,et al.  On sequential simulation-based methods for Bayesian filtering , 1998 .

[23]  Yu Hen Hu,et al.  Energy-Based Collaborative Source Localization Using Acoustic Microsensor Array , 2003, EURASIP J. Adv. Signal Process..

[24]  Kai-Ten Feng,et al.  GALE: An Enhanced Geometry-Assisted Location Estimation Algorithm for NLOS Environments , 2008, IEEE Transactions on Mobile Computing.

[25]  S. Georges,et al.  Fingerprinting Localization Using Ultra-Wideband and Neural Networks , 2007, 2007 International Symposium on Signals, Systems and Electronics.

[26]  Hugh F. Durrant-Whyte,et al.  A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..

[27]  Pravin Varaiya,et al.  Stochastic Systems: Estimation, Identification, and Adaptive Control , 1986 .

[28]  Daniel Streller.  Road map assisted ground target tracking , 2008, 2008 11th International Conference on Information Fusion.

[29]  Ding-Bing Lin,et al.  Mobile location estimation based on differences of signal attenuations for GSM systems , 2003, IEEE Antennas and Propagation Society International Symposium. Digest. Held in conjunction with: USNC/CNC/URSI North American Radio Sci. Meeting (Cat. No.03CH37450).

[30]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[31]  Thiagalingam Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation , 2001 .

[32]  Rudolph van der Merwe,et al.  Sigma-point kalman filters for probabilistic inference in dynamic state-space models , 2004 .

[33]  T. Singh,et al.  Efficient particle filtering for road-constrained target tracking , 2005 .

[34]  Branko Ristic,et al.  A variable structure multiple model particle filter for GMTI tracking , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[35]  N. Gordon,et al.  Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .

[36]  Hans Driessen,et al.  MAP estimation in particle filter tracking , 2008 .

[37]  Bernard Mulgrew,et al.  Variable-Mass Particle Filter for Road-Constrained Vehicle Tracking , 2008, EURASIP J. Adv. Signal Process..

[38]  K.J.R. Liu,et al.  Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs , 2005, IEEE Signal Processing Magazine.

[39]  M. Melamed.  Detection , 2021, SETI: Astronomy as a Contact Sport.

[40]  T. Zadra,et al.  Precision tracking of ground targets , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[41]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[42]  O. Sallent,et al.  A mobile location service demonstrator based on power measurements , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[43]  M. Hata,et al.  Empirical formula for propagation loss in land mobile radio services , 1980, IEEE Transactions on Vehicular Technology.

[44]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[45]  Neil J. Gordon,et al.  Editors: Sequential Monte Carlo Methods in Practice , 2001 .

[46]  M. Ulmke,et al.  Road-map assisted ground moving target tracking , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[47]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[48]  Tomoaki Ohtsuki,et al.  RSS-Based Localization in Environments with Different Path Loss Exponent for Each Link , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.