Gaussian Process Assisted Fingerprinting Localization

This paper presents an application of the firefly algorithm (FA) to Gaussian process (GP)-based localization. Partial radio-frequency (RF) signature map is first collected and used to train the GP model. The hyperparameters of the GP prior model are searched by the FA. GP regression is then used to generate an estimation of the RF signature map for the entire area to be localized. This is in contrast to traditional fingerprinting-based localization where a database of RF signature has to be collected for the entire area of interest. Using the estimated signature map, the position of the device is estimated using a combined likelihood function from multiple access points (APs). The proposed scheme relies on only existing infrastructures and can be used both indoor and outdoor. Experiments using indoor WiFi APs show that median error is around 3 m.

[1]  Alexei Makarenko,et al.  Gaussian Process Models for Indoor and Outdoor Sensor-Centric Robot Localization , 2008, IEEE Transactions on Robotics.

[2]  H. Laitinen,et al.  Database correlation method for GSM location , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[3]  Yunhao Liu,et al.  WILL: Wireless indoor localization without site survey , 2012, 2012 Proceedings IEEE INFOCOM.

[4]  Yunhao Liu,et al.  From RSSI to CSI , 2013, ACM Comput. Surv..

[5]  Hiroshi Ban,et al.  Gaussian processes for learning-based indoor localization , 2011, 2011 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC).

[6]  Felix Duvallet,et al.  WiFi position estimation in industrial environments using Gaussian processes , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Eyal de Lara,et al.  Accurate GSM Indoor Localization , 2005, UbiComp.

[8]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[9]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[10]  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).

[11]  S. Ahonen,et al.  Database correlation method for UMTS location , 2001, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[12]  Moustafa Youssef,et al.  WLAN location determination via clustering and probability distributions , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[13]  Israel Cohen,et al.  Single-Site Emitter Localization via Multipath Fingerprinting , 2013, IEEE Transactions on Signal Processing.

[14]  E KavrakiLydia,et al.  Robotics-based location sensing using wireless Ethernet , 2005 .

[15]  M. Nezafat,et al.  Localization of wireless terminals using subspace matching with ray-tracing-based simulations , 2004, Processing Workshop Proceedings, 2004 Sensor Array and Multichannel Signal.

[16]  Xin-She Yang,et al.  Firefly Algorithm: Recent Advances and Applications , 2013, ArXiv.

[17]  Dieter Fox,et al.  Gaussian Processes for Signal Strength-Based Location Estimation , 2006, Robotics: Science and Systems.

[18]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[19]  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..

[20]  Anshul Rai,et al.  Zee: zero-effort crowdsourcing for indoor localization , 2012, Mobicom '12.

[21]  Kostas E. Bekris,et al.  On the feasibility of using wireless ethernet for indoor localization , 2004, IEEE Transactions on Robotics and Automation.

[22]  Joseph Kee-Yin Ng,et al.  Providing location services within a radio cellular network using ellipse propagation model , 2005, 19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers).

[23]  Dileeka Dias,et al.  Integration of fingerprinting and trilateration techniques for improved indoor localization , 2010, 2010 Seventh International Conference on Wireless and Optical Communications Networks - (WOCN).

[24]  Eyal de Lara,et al.  GSM indoor localization , 2007, Pervasive Mob. Comput..

[25]  Yu-Chee Tseng,et al.  Design and implementation of a self-guided indoor robot based on a two-tier localization architecture , 2012, Pervasive Mob. Comput..

[26]  Hugh F. Durrant-Whyte,et al.  A solution to the simultaneous localization and map building (SLAM) problem , 2001, IEEE Trans. Robotics Autom..

[27]  Tin Kam Ho,et al.  SignalSLAM: Simultaneous localization and mapping with mixed WiFi, Bluetooth, LTE and magnetic signals , 2013, International Conference on Indoor Positioning and Indoor Navigation.

[28]  Neil D. Lawrence,et al.  WiFi-SLAM Using Gaussian Process Latent Variable Models , 2007, IJCAI.

[29]  Christian Hoene,et al.  Measuring Round Trip Times to Determine the Distance Between WLAN Nodes , 2005, NETWORKING.