Location Characterization in Noisy Range Network Localization

DOI: 10.4236/jcc.2015.311020   PDF   HTML   XML   2,370 Downloads   2,707 Views   Citations

Abstract

Network localization is a fundamental problem in wireless sensor networks, mainly in location dependent applications. A common family of solutions to this problem is the range-based network localization. The resulting localization algorithms are noise sensitive and thus lacking in terms of robustness. Our contribution provides an algorithm which is robust to measurement errors. We propose an analytical tool to analyze the effect of range errors in the final location and use a distributed method to solve the noisy range localization problem.

Share and Cite:

Wei, M. , Chellali, R. , Yi, Y. , Wang, T. and Qin, W. (2015) Location Characterization in Noisy Range Network Localization. Journal of Computer and Communications, 3, 126-132. doi: 10.4236/jcc.2015.311020.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Patwari, N., Hero III, A.O., Perkins, M., Correal, N.S. and O’dea, R.J. (2003) Relative Location Estimation in Wireless Sensor Networks. IEEE Transactions on Signal Processing, 51, 2137-2148. http://dx.doi.org/10.1109/TSP.2003.814469
[2] Savvides, A., Garber, W.L., Moses, R.L. and Srivastava, M.B. (2005) An Analysis of Error Inducing Parameters in Multihop Sensor Node Localization. IEEE Transactions on Mobile Computing, 567-577. http://dx.doi.org/10.1109/TMC.2005.78
[3] Anderson, B.D.O., Shames, I., Mao, G. and Fidan, B. (2010) Formal Theory of Noisy Sensor Network Localization. SIAM Journal of Discrete Mathematic, 24, 684-698. http://dx.doi.org/10.1137/100792366
[4] Moore, D., Leonard, J., Rus, D. and Teller, S. (2004) Robust Distributed Network Localization with Noisy Range Measurements. Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, 50-61. http://dx.doi.org/10.1145/1031495.1031502
[5] Cao, M., Anderson, B. and Morse, A.S. (2006) Sensor Network Lo-calization with Imprecise Distances. Systems & Control Letters, 55, 887-893. http://dx.doi.org/10.1016/j.sysconle.2006.05.004
[6] Shames, I. and Bishop, A.N. (2011) Noisy Network Localization via Optimal Measurement Refinement Part 2: Distance-Only Network Localization. 18th World Congress of the International Federation of Automatic Control (IFAC).
[7] Biswas, P., Liang, T.C., Toh, K.C., Ye, Y. and Wang, T.C. (2006) Semidefinite Programming Approaches for Sensor Network Localization with Noisy Distance Measurements. IEEE Transactions on Automation Science and Engineering, 3, 360-371. http://dx.doi.org/10.1109/TASE.2006.877401
[8] Calafiore, G.C., Carlone, L. and Wei, M. (2010) A Distributed Gradient Method for Localization of Formations Using Relative Range Measurements. IEEE Multi-Conference on Systems and Control (MSC), 1146-1151. http://dx.doi.org/10.1109/CACSD.2010.5612764
[9] Eren, T., Goldenberg, D.K., Whiteley, W., Yang, Y.R., Morse, A.S., Anderson, B.D.O. and Belhumeur, P.N. (2004) Rigidity, Computation, and Randomization in Network Localiza-tion. IEEE INFOCOM, 2673-2684. http://dx.doi.org/10.1109/infcom.2004.1354686
[10] Shames, I., Fidan, B.I. and Anderson, B. (2009) Minimization of the Effect of Noisy Measurements on Localization of Multi-Agent Autonomous Formations. Automatica, 45, 1058-1065. http://dx.doi.org/10.1016/j.automatica.2008.11.018

  
comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.