A grid-based indoor radiolocation technique based on spatially coherent path loss model

This paper presents a grid-based indoor radiolocation technique based on a Spatially Coherent Path Loss Model (SCPL). Received Signal Strength (RSS) fingerprints are collected at different positions in the environment from which the radio wave propagation for the environment is empirically approximated with the SCPL model. Unlike the conventional path loss models, SCPL approximates radio wave propagation by first dividing the localization environment into grid cells and estimating the model parameters for each grid cell. Thus, the proposed technique is able to account for attenuation, resulting from non-uniform environmental irregularities. The efficacy of the proposed technique was investigated with an experiment comparing SCPL and an indoor radiolocation technique based on a conventional path loss model. The comparison has indicated the improved performance of the SCPL by up to 44%.

[1]  John S. Seybold,et al.  Introduction to RF Propagation: Seybold/Introduction to RF Propagation , 2005 .

[2]  Kaishun Wu,et al.  FIFS: Fine-Grained Indoor Fingerprinting System , 2012, 2012 21st International Conference on Computer Communications and Networks (ICCCN).

[3]  Geoffrey E. Hinton,et al.  Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.

[4]  Nitin H. Vaidya,et al.  Proceedings of the sixteenth annual international conference on Mobile computing and networking , 2010, MobiCom 2010.

[5]  William S. Murphy,et al.  Determination of a Position in Three Dimensions using Trilateration and Approximate Dis- tances , 1995 .

[6]  Venkata N. Padmanabhan,et al.  Indoor localization without the pain , 2010, MobiCom.

[7]  Shiwen Mao,et al.  CSI-Based Fingerprinting for Indoor Localization: A Deep Learning Approach , 2016, IEEE Transactions on Vehicular Technology.

[8]  Simo Ali-Löytty,et al.  A comparative survey of WLAN location fingerprinting methods , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[9]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[10]  Yosef Pinhasi,et al.  Atmospheric and Fog Effects on Ultra-Wide Band Radar Operating at Extremely High Frequencies , 2016, Sensors.

[11]  Moustafa Youssef,et al.  The Horus WLAN location determination system , 2005, MobiSys '05.

[12]  José M. Alonso,et al.  A multiclassifier approach for topology-based WiFi indoor localization , 2013, Soft Computing.

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

[14]  PROPAGATION DATA AND PREDICTION METHODS FOR THE PLANNING OF INDOOR RADIOCOMMUNICATION SYSTEMS AND RADIO LOCAL AREA NETWORKS IN THE FREQUENCY RANGE 900 MHz TO 100 GHz , 1997 .

[15]  J. Seybold Introduction to RF Propagation , 2005 .

[16]  Tom Minka,et al.  You are facing the Mona Lisa: spot localization using PHY layer information , 2012, MobiSys '12.

[17]  François Marx,et al.  Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning , 2006, EURASIP J. Adv. Signal Process..

[18]  V. Padmanabhan,et al.  Enhancements to the RADAR User Location and Tracking System , 2000 .

[19]  Subrata Goswami Indoor Location Technologies , 2012 .

[20]  S. Venkatraman,et al.  statistical approach to non-line-of-sight BS identification , 2002, The 5th International Symposium on Wireless Personal Multimedia Communications.

[21]  Yoshua Bengio,et al.  Greedy Layer-Wise Training of Deep Networks , 2006, NIPS.

[22]  Hao Jiang,et al.  Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization , 2015, Sensors.

[23]  Sachin Katti,et al.  SpotFi: Decimeter Level Localization Using WiFi , 2015, SIGCOMM.

[24]  Luis E. Ortiz,et al.  WiGEM: a learning-based approach for indoor localization , 2011, CoNEXT '11.

[25]  Haiyun Luo,et al.  Zero-Configuration, Robust Indoor Localization: Theory and Experimentation , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[26]  Swarun Kumar,et al.  Accurate indoor localization with zero start-up cost , 2014, MobiCom.

[27]  Wee-Seng Soh,et al.  A survey of calibration-free indoor positioning systems , 2015, Comput. Commun..

[28]  Jie Xiong,et al.  ArrayTrack: A Fine-Grained Indoor Location System , 2011, NSDI.

[29]  W. Bachtold,et al.  Microwave backscatter modulation systems , 2000, 2000 IEEE MTT-S International Microwave Symposium Digest (Cat. No.00CH37017).

[30]  T. Manabe,et al.  Measurement of the complex refractive index of concrete at 57.5 GHz , 1996 .

[31]  Swarun Kumar,et al.  LTE radio analytics made easy and accessible , 2014 .

[32]  Avinash C. Kak,et al.  Vision for Mobile Robot Navigation: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Fadel Adib,et al.  See through walls with WiFi! , 2013, SIGCOMM.

[34]  Yongqiang Hei,et al.  Identification and mitigation of NLOS based on channel state information for indoor WiFi localization , 2015, 2015 International Conference on Wireless Communications & Signal Processing (WCSP).

[35]  Joseph Kee-Yin Ng,et al.  Location Estimation via Support Vector Regression , 2007, IEEE Transactions on Mobile Computing.

[36]  Shiwen Mao,et al.  PhaseFi: Phase Fingerprinting for Indoor Localization with a Deep Learning Approach , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[37]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[38]  Jue Wang,et al.  Dude, where's my card?: RFID positioning that works with multipath and non-line of sight , 2013, SIGCOMM.

[39]  Benoit Denis,et al.  Impact of NLOS propagation upon ranging precision in UWB systems , 2003, IEEE Conference on Ultra Wideband Systems and Technologies, 2003.

[40]  Swarun Kumar,et al.  Decimeter-Level Localization with a Single WiFi Access Point , 2016, NSDI.

[41]  Aboelmagd Noureldin,et al.  Dynamic Online-Calibrated Radio Maps for Indoor Positioning in Wireless Local Area Networks , 2013, IEEE Transactions on Mobile Computing.

[42]  Shueng-Han Gary Chan,et al.  Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons , 2016, IEEE Communications Surveys & Tutorials.

[43]  Weihua Zhuang,et al.  Nonline-of-sight error mitigation in mobile location , 2004, IEEE INFOCOM 2004.

[44]  Pi-Chun Chen,et al.  A non-line-of-sight error mitigation algorithm in location estimation , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[45]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[46]  Theodore S. Rappaport,et al.  Propagation measurements and models for wireless communications channels , 1995, IEEE Commun. Mag..

[47]  Rongke Liu,et al.  Wi-Fi-Based Localization in Dynamic Indoor Environment Using a Dynamic Neural Network , 2013 .

[48]  L. C. Mak Non-Line-of-Sight Localisation of a Sound Source , 2009 .

[49]  H.T. Friis,et al.  A Note on a Simple Transmission Formula , 1946, Proceedings of the IRE.

[50]  N.B. Mandayam,et al.  Decision theoretic framework for NLOS identification , 1998, VTC '98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No.98CH36151).