Comparison of orientation-aware RSS-based localization algorithms

ABSTRACT

A large number of researches have been focused on indoor location tracking system over the past years. There are theoretical and empirical RSS-based algorithms proposed and many studies have been made by comparing the performance of these algorithms. However, there is a lack of theoretical basis and understanding on the orientation of the user. This paper presents a model for an orientation-aware indoor location tracking system using wireless sensors based on IEEE 802.15.4 standard protocol. For path loss model, our experiment shows a better prediction of RSS when attenuation factors for different orientations are considered in the model. On the other hand, orientation-aware fingerprint algorithm, which currently stands as one of the most accurate RSS-based localization algorithm, is also examined in our experiment to have a basis of comparison with an empirical algorithm.

REFERENCES

• 1: Bahl, P., and Padmanabhan, V. N. 2000. RADAR: An In-Building RF-based User Location and Tracking System. INFOCOM 2000. 19th Annual Joint Conf. of the IEEE Computer and Communications Societies. Proceedings, 2, (Mar. 2000), pp. 775--784.
• 2: Bahl, P., and Padmanabhan, V. N. 2000. Enhancements of the RADAR User Location and Tracking System. Technical Report MSR-TR-2000-12, Microsoft Research, Microsoft Corporation One Microsoft Way Redmond, WA 98052 (2000).
• 3: Paul Castro , Patrick Chiu , Ted Kremenek , Richard R. Muntz, A Probabilistic Room Location Service for Wireless Networked Environments, Proceedings of the 3rd international conference on Ubiquitous Computing, p.18-34, September 30-October 02, 2001, Atlanta, Georgia, USA
• 4: CC2420 2.4 GHz IEEE 802.15.4/Zigbee-ready RF Transceiver. 2007. Chipcon Products from Texas Instruments Incorporated (Mar. 2007). http://ti.com/lit/gpn/cc2420
• 5: Hyunggi Cho , Myungseok Kang , Jonghyuk Park , Byungsung Park , Hagbae Kim, Performance Analysis of Location Estimation Algorithm in ZigBee Networks Using Received Signal Strength, Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops, p.302-306, May 21-23, 2007 [doi>10.1109/AINAW.2007.283]
• 6: Janssen, G. J. M., and Prasad, R. 1992. Propagation Measurements in an Indoor Radio Environment at 2.4 GHz, 4.75 GHz and 11.5 GHz. IEEE 42nd Vehicular Technology Conf., 2, (May, 1992) 617--620 DOI= 10.1109/VETEC.1992.245320.
• 7: Kaemarungi, K., and Krishnamurthy, P. 2004. Modeling of Indoor Positioning Systems Based on Location Fingerprinting. INFOCOM 2004, 2 (Mar. 2004), 1023--1022.
• 8: Thomas King , Stephan Kopf , Thomas Haenselmann , Christian Lubberger , Wolfgang Effelsberg, COMPASS: A probabilistic indoor positioning system based on 802.11 and digital compasses, Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation & characterization, September 29-29, 2006, Los Angeles, CA, USA [doi>10.1145/1160987.1160995]
• 9: Marc Lihan , Takeshi Tsuchiya , Keiichi Koyanagi, Orientation-Aware Indoor Localization Path Loss Prediction Model for Wireless Sensor Networks, Proceedings of the 2nd international conference on Network-Based Information Systems, September 01-05, 2008, Turin, Italy [doi>10.1007/978-3-540-85693-1_19]
• 10: Madigan, D., Elnahrawy E., and Martin, R. 2005. Bayesian Indoor Positioning Systems. INFOCOM 2005, 24th Annual Joint Conf. of the IEEE Computer and Communications Societies, Proc. IEEE, 2, (Miami, Florida, Mar. 2005) 1217--1227.
• 11: Prasithsangaree P., Krishnamurthy, P., and Chrysanthis, P. 2002. On Indoor Position Location with WLANS. The 13th IEEE Int'l Symposium on Personal, Indoor Mobile Radio Communications, 2, (Sept. 2002), 720--724.
• 12: Nissanka B. Priyantha , Anit Chakraborty , Hari Balakrishnan, The Cricket location-support system, Proceedings of the 6th annual international conference on Mobile computing and networking, p.32-43, August 06-11, 2000, Boston, Massachusetts, United States [doi>10.1145/345910.345917]
• 13: Seidel, S. Y., and Rappaport, T. S.: 914 MHz Path Loss Prediction Models for Indoor Wireless Communications in Multi-floored Buildings. 1992. IEEE Transaction on Antennas and Propagation, 40, 2, (Feb. 1992) 207--217. DOI= 10.1109/8.127405.
• 14: Sun Microsystems, Small Programmable Object Technology, http://www.sunspotworld.com.
• 15: Roy Want , Andy Hopper , Veronica Falcão , Jonathan Gibbons, The active badge location system, ACM Transactions on Information Systems (TOIS), v.10 n.1, p.91-102, Jan. 1992 [doi>10.1145/128756.128759]

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Wireless communication

Additional Classification:
  C. Computer Systems Organization
  C.3 SPECIAL-PURPOSE AND APPLICATION-BASED SYSTEMS
      Subjects: Signal processing systems

General Terms:
Algorithms, Design, Experimentation, Measurement

Keywords:
ZigBee, localization, orientation-aware, path loss, positioning system, tracking system