Open Access Open Access  Restricted Access Subscription Access

ENHANCING THE COVERAGE OF INDOOR RADIO LOCALIZATION BY DISTRIBUTED COMPUTATIONS

Andreas Fink, Helmut Beikirch

Abstract


The prevalent evaluation criterion for indoor local positioning systems (ILPS) is the achievable accuracy in terms of Euclidean distance between estimated and true position. Systems relying on received signal strength (RSS) ranging often use a distributed collection of RSS sensor data at reference nodes and a centralized position estimation. For this direct remote positioning, the accuracy is dependent on the reference node density and thus, is indirect proportional to the achievable coverage. To split up the dependency between these two criteria, we propose a distributed weighted centroid localization (dWCL) strategy with a hierarchical sensor data field bus. Accuracy and coverage of centralized and distributed WCL algorithms are compared for a one-dimensional tracking simulation and 196 reference nodes, arranged in up to 28 gateway segments. Using distributed computations, the localization system’s coverage is increased by factor ten while the location estimation error increases only slightly.

Keywords


Centroid Localization; Distributed Computing; Human Tracking; RSS Ranging.

Full Text:

PDF

References


Z. Sun and I. F. Akyildiz, Channel modeling and analysis for wireless networks in underground mines and road tunnels, IEEE Transactions on Communication, (58) 6 (2010), pp. 1758–1768.

J. Figueiras and S. Frattasi, Mobile Positioning and Tracking - From Conventional to Cooperative Techniques, 2010.

A. Fink and H. Beikirch, Adding link quantity information to redundant RF signal strength estimates for improved indoor positioning, 3rd IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2012, pp. 1–6.

ISO 11898-1, Road Vehicles – Controller Area Network – Part 1: Data Link Layer and Physical Signaling, ISO Std., 2003.

A. Fink and H. Beikirch, Combining of redundant signal strength readings for an improved RF localization in multipath indoor environments, 15th International Conference on Information Fusion, 2012, pp. 1–7.

A. Fink and H. Beikirch, Radio-based human tracking for large indoor environments using distributed centroid location estimation, 7th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2013, pp. 442-449.

R. Mautz, Indoor Positioning Technologies, Habilitation Thesis, 2012.

T. K. Kohoutek, R. Mautz, and A. Donaubauer, Real-time indoor positioning using range imaging sensors, Proceedingsd of SPIE Photonics, (7724) (2010).

M. Allen, S. Baydere, E. Gaura, and G. Kucuk, Evaluation of localization algorithms, Localization Algorithms and Strategies for Wireless Sensor Networks: Monitoring and Surveillance Techniques for Target Tracking, 2009, pp. 348–379.

P. Barsocchi, S. Chessa, and F. Furfari, Evaluating AAL solutions through competitive benchmarking: the localization competition. IEEE Pervasive Computing, (99) (2013).

A. Fink, H. Beikirch, and M. Voss, Improved indoor localization with diversity and filtering based on received signal strength measurements, International Journal of Computing, (9) 1 (2010).

T. S. Rappaport, Wireless Communications – Principles and Practice, Prentice Hall PTR, 2002.

H. Benn and H. Thomas, GSM in the indoor business environment, in GSM Evolution Towards 3rd Generation Systems, Z. Zyonar, P. Jung, and K. Kammerlander, Eds. Kluwer Academic Publishers, 2002, pp. 211–234.

D. Cheung and C. Prettie, A path loss comparison between the 5 GHz UNII band (802.11a) and the 2.4 GHz ISM band (802.11b). Intel Labs, Technical Report, 2002.

T. S. Rappaport and C. D. McGillem, UHF fading in factories, IEEE Journal of Selected Areas Communications, (7) 1 (1989), pp. 40–48.

Texas Instruments, CC2500: low-cost low-power 2.4 GHz RF transceiver. rev. C, 2008.

C. Beder, A. McGibney, and M. Klepal, Predicting the expected accuracy for fingerprinting based WiFi localisation systems, 2nd IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2011, pp. 1–6.

A. Abdi, C. Tepedelenlioglu, M. Kaveh, and G. Giannakis, On the estimation of the parameter for the rice fading distribution, IEEE Communication Letteers, (5) 3 (2001), pp. 92–94.

A. T. Parameswaran, M. I. Husain, and S. Upadhyaya, Is RSSI a reliable parameter in sensor localization algorithms, an experimental study, IEEE International Symposium on Reliable Distributed Systems, 2009.

E. Elnahrawy, X. Li, and R. P. Martin, The limits of localization using signal strength: A comparative study, IEEE Sensor and Ad Hoc Communications and Networks (SECON), 2004, pp. 406-414.

K. Whitehouse, C. Karlof, and D. Culler, A practical evaluation of radio signal strength for ranging-based localization, SIGMOBILE Mobile Computing and Communications Review, (11) (January 2007), pp. 41-52.

G. Chandrasekaran, M. A. Ergin, J. Yang, S. Liu, Y. Chen, M. Gruteser, and R. P. Martin, Empirical evaluation of the limits on localization using signal strength, IEEE Sensor and Ad Hoc Communications and Networks (SECON), 2009.

Y. P. Zhang, G. X. Zheng, and J. H. Sheng, Radio propagation at 900 MHz in underground coal mines, IEEE Transactions on Antennas Propagation, (49) 5 (2001), pp. 757–762.

M. Boutin, A. Benzakour, C. Despins, and S. Affes, Characterization and modeling of a wireless channel at 2.4 and 5.8 GHz in underground tunnels, 3rd International Symposium on Wireless Communication Systems (ISWCS), 2006, pp. 517-521.

K. Tindell and A. Burns, Guaranteed message latencies for distributed safety-critical hard real-time control networks. Technical Report, 1994.

A. Fink and H. Beikirch, RSSI-based indoor localization using antenna diversity and plausibility filter, 6th Workshop on Positioning Navigation and Communication, 2009, pp. 159–165.

A. Fink and H. Beikirch, Analysis of RSS-based location estimation techniques in fading environments, 2nd IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2011, pp. 1–6.


Refbacks

  • There are currently no refbacks.