Research Article | OPEN ACCESS
On Location Estimation Methods for Mobile Wireless Sensor Nodes
Marwan Al-Jemeli and Fawnizu Azmadi Hussin
Department of Electrical and Electronic Engineering, Centre for Intelligent Signal and Imaging Research (CISIR), Universiti Teknologi Petronas, Bandar Seri Iskandar, 31750 Tronoh, Perak, Malaysia
Research Journal of Applied Sciences, Engineering and Technology 2014 1:124-130
Received: March 29, 2014 | Accepted: May 09, 2014 | Published: July 05, 2014
Abstract
This study presents an energy-efficient location estimation method aimed for mobile nodes in wireless sensor networks. The proposed method is a combination of two operations. Trilateration method is combined with a vector based incremental updates which is implemented by using a digital compass and a speedometer to estimate the location of the mobile node. This combined operation decreases the power consumed from the mobile node trying to locate itself. The proposed method has been implemented on an arduino-based mobile robot with wireless communication peripherals. The implementation shows that the location estimation accuracy is between 0.69-1.97 m from the actual location of the mobile node. The average location estimation error is comparable to other proposed methods for locating mobile sensor nodes. Based on the actual measurement of the test system, the energy consumption of the proposed method is 20% less than the trilateration method alone.
Keywords:
Digital compass, energy , localization , trilateration , wireless sensor networks,
References
-
Al-Jemeli, M., F.A. Hussin and B.B. Samir, 2012. An energy efficient localization estimation approach for mobile wireless sensor networks. Proceeding of the 4th International Conference on Intelligent and Advanced Systems (ICIAS, 2012). Kuala Lumpur, 1: 301-306.
CrossRef -
Amundson, I., J. Sallai, X. Koutsoukos, A. Ledeczi and M. Maroti, 2011. RF angle of arrival-based node localisation. Int. J. Sens. Netw., 9: 209-224, Doi: 10.1504/ijsnet.2011.040241.
CrossRef -
Baggio, A. and K. Langendoen, 2008. Monte Carlo localization for mobile wireless sensor networks. Ad Hoc Netw., 6(5): 718-733.
CrossRef -
Boukerche, A., H.A.B. Oliveira, E.F. Nakamura and A.A.F. Loureiro, 2007. Localization systems for wireless sensor networks. IEEE Wirel. Commun., 14(6): 6-12.
CrossRef -
Chan, Y.W.E. and S. Boon Hee, 2011. A new lower bound on range-free localization algorithms in wireless sensor networks. IEEE Commun. Lett., 15(1): 16-18.
CrossRef -
Chen, W. and X. Li, 2007. Sensor localization under limited measurement capabilities. IEEE Network, 21: 16-23.
CrossRef -
Chia-Ho, O., 2011. A localization scheme for wireless sensor networks using mobile anchors with directional antennas. IEEE Sens. J., 11(7): 1607-1616.
CrossRef -
Guvenc, I. and C. Chia-Chin, 2009. A survey on TOA based wireless localization and NLOS mitigation techniques. IEEE Commun. Surv. Tutorial, 11(3): 107-124.
CrossRef -
Jie Yang, Y.C., 2011. Improving localization accuracy of RSS-based lateration methods in indoor environments. Ad Hoc Sens. Wirel. Ne., 11(3/4): 307-329.
-
Jingjing, G., C. Songcan and S. Tingkai, 2011. Localization with incompletely paired data in complex wireless sensor network. IEEE T. Wirel. Commun., 10: 2841-2849.
CrossRef -
Khan, U.A., S. Kar and J.M.F. Moura, 2009. Distributed sensor localization in random environments using minimal number of anchor nodes. IEEE T. Signal Proces., 57: 2000-2016.
-
Kim, H. and J.S. Choi, 2008. Advanced indoor localization using ultrasonic sensor and digital compass. Proceeding of the International Conference on Control, Automation and Systems (ICCAS, 2008). Seoul, pp: 223-226.
-
Lee, K.W., J.B. Park and B.H. Lee, 2008. Dynamic localization with hybrid trilateration for mobile robots in intelligent space. Intell. Serv. Robot, 1: 221-235.
CrossRef -
Mao, G., B. Fidan and B.D.O. Anderson, 2007. Wireless sensor network localization techniques. Comput. Netw., 51: 2529-2553.
CrossRef -
Oberholzer, G., P. Sommer and R. Wattenhofer, 2011. SpiderBat: Augmenting wireless sensor networks with distance and angle information. Proceeding of the 10th International Conference on Information Processing in Sensor Networks (IPSN, 2011). Chicago, IL, pp: 211-222.
-
Paul, A.S. and E.A. Wan, 2009. RSSI-based indoor localization and tracking using sigma-point Kalman smoothers. IEEE J. Sel. Top. Signa., 3(5): 860-873.
CrossRef -
Sun, Z., R. Farley, T. Kaleas, J. Allis and K. Chikkappa, 2011. Cortina: Collaborative context-aware indoor positioning employing RSS and RToF techniques. Proceeding of the 9th Annual IEEE International Conference on Pervasive Computing and Communications (PerCom, 2011). Seattle, WA, USA, March 21-25, pp: 340-343.
-
Win, M.Z., A. Conti, S. Mazuelas, Y. Shen, W.M. Gifford, D. Dardari and M. Chiani, 2011. Network localization and navigation via cooperation. IEEE Commun. Mag., 49(5): 56-62.
CrossRef -
Xinrong, L., 2006. RSS-based location estimation with unknown pathloss model. IEEE T. Wirel. Commun., 5: 3626-3633.
CrossRef -
Xinrong, L., 2007. Collaborative localization with received-signal strength in wireless sensor networks. IEEE T. Veh. Technol., 56: 3807-3817.
CrossRef
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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