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A Novel Method to Select Minimum Neighbors in Cooperative Localization Network

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Abstract

Cooperative localization is an emerging paradigm that circumvents the needs for high-power, high-density anchor deployment, and offers additional positioning accuracy by exchanging information between adjacent agents. Considering that positioning accuracy only need to meet the application requirements, too high positioning accuracy means that too much redundant information is exchanged. This paper presents a neighbors selection algorithm that tries to meet the positioning accuracy required by an application , while the system consumption is optimized. More specifically, this proposed algorithm tries to minimize the number of neighbors involved in cooperation on the basis of the equivalent Fisher information matrix. Before putting forward the algorithm, we first introduce the notion of equivalent Fisher information and characterize localization accuracy called the squared position error bound. Then we find that not only the Fisher information of neighbor nodes determines the positioning accuracy of the agent to be located, but also the direction of Fisher information affected the positioning accuracy. Based on this, an algorithm for selecting the minimum cooperative subset is proposed. Simulation results show that the proposed algorithm can obviously improving the utilization of energy compared to other commonly used methods by exchanging information with a few nodes, while achieving the specified positioning accuracy.

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References

  1. S. Gezici, Zhi Tian, G. B. Giannakis, H. Kobayashi, A. F. Molisch, H. V. Poor and Z. Sahinoglu, Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks, IEEE Signal Processing Magazine., Vol. 22, No. 4, pp. 70–84, 2005.

    Article  Google Scholar 

  2. Y. Qi, H. Kobayashi and H. Suda, On time-of-arrival positioning in a multipath environment, IEEE Transactions on Vehicular Technology, Vol. 55, No. 5, p. pp. 1516C1526, 2006.

    Article  Google Scholar 

  3. T. S. Rappaport, J. H. Reed, and B. D. Woerner, Position location using wireless communications on highways of the future, IEEE Communications Magazine, vol. 34, no. 10, pp. 33C41, Oct 1996.

  4. D. Niculescu and B. Nath, Ad hoc positioning system (aps) using aoa, in IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428), vol. 3, March 2003, pp. 1734C1743 vol.3.

  5. S. Uluskan and T. Filik, A survey on the fundamentals of rss based localization, in 2016 24th Signal Processing and Communication Application Conference (SIU), May 2016, pp. 1633C1636.

  6. Z. C. J. Milliken R J, Global positioning system. The Institute of Navigation, Washington, DC, 1980. pp. pp. 12C14,

  7. C. Liu, D. Fang, Z. Yang, H. Jiang, X. Chen, W. Wang, T. Xing and L. Cai, Rss distribution-based passive localization and its application in sensor networks, IEEE Transactions on Wireless Communications, Vol. 15, No. 4, p. pp. 2883C2895, 2016.

    Google Scholar 

  8. L. Taponecco, A. A. DAmico and U. Mengali, Joint toa and aoa estimation for uwb localization applications, IEEE Transactions on Wireless Communications, Vol. 10, No. 7, p. pp. 2207C2217, 2011.

    Article  Google Scholar 

  9. N. Patwari, J. N. Ash, S. Kyperountas, A. O. Hero, R. L. Moses and N. S. Correal, Locating the nodes: cooperative localization in wireless sensor networks, IEEE Signal Processing Magazine, Vol. 22, No. 4, p. pp. 54C69, 2005.

    Article  Google Scholar 

  10. Y. Shen, H. Wymeersch, and M. Z. Win, Fundamental limits of wideband localization-part ii: Cooperative networks, IEEE Transactions on Information Theory, vol. 56, no. 10, pp. 4981C5000, Oct 2010.

  11. T. V. Nguyen, Y. Jeong, H. Shin and M. Z. Win, Least square cooperative localization, IEEE Transactions on Vehicular Technology, Vol. 64, No. 4, p. pp. 1318C1330, 2015.

    Article  Google Scholar 

  12. H. Wymeersch, J. Lien, and M. Z. Win, Cooperative localization in wireless networks, Proceedings of the IEEE, vol. 97, no. 2, pp. 427C 450, Feb 2009.

  13. K. Raghava Rao, T. Ravi Kumar, and C. Venkatnaryana, Selection of Anchor Nodes in Time of Arrival for Localization in Wireless Sensor Networks, 2016, pp. 45C57.

  14. A. T. Ihler, J. W. Fisher, R. L. Moses and A. S. Willsky, Nonparametric belief propagation for self-localization of sensor networks, IEEE Journal on Selected Areas in Communications, Vol. 23, No. 4, p. pp. 809C819, 2005.

    Article  Google Scholar 

  15. V. Savic and S. Zazo, Reducing communication overhead for cooperative localization using nonparametric belief propagation, IEEE Wireless Communications Letters, vol. 1, no. 4, pp. 308C311, August 2012.

  16. Y. Yong and M. Lingjuan, Gdop results in all-in-view positioning and in four optimum satellites positioning with gps prn codes ranging, in PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556), April 2004, pp. 723C727.

  17. A. Peng, G. Ou and G. Li, Fast satellite selection method for multiconstellation global navigation satellite system under obstacle environments, IET Radar, Sonar Navigation, Vol. 8, No. 9, p. pp. 1051C1058, 2014.

    Article  Google Scholar 

  18. W. Xiaoming, W. Hua, L. Yang, and W. Ran, An improved localization scheme based on anchor selection in wireless sensor networks, in 2012 International Conference on Computer Science and Service System, Aug 2012, pp. 899C902.

  19. X. M. Li, Y. J. Wang, Z. C. Dai, and K. G. Qian, An improved bounding box localization algorithm based on optimum node selection, in Mechanical Components and Control Engineering III, ser. Applied Mechanics and Materials, vol. 668. Trans Tech Publications, 11 2014, pp. 1359C1362.

  20. S. Tomic, M. Beko, and R. Dinis, Distributed RSS-Based Localization in Wireless Sensor Networks with Node Selection Mechanism, 2015, pp. 204C214.

  21. M. Dai, F. Sottile, M. A. Spirito, and R. Garello, An energy efficient tracking algorithm in uwb-based sensor networks, in 2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Oct 2012, pp. 173C178.

  22. K. Das and H. Wymeersch, Censoring for bayesian cooperative positioning in dense wireless networks, IEEE Journal on Selected Areas in Communications, vol. 30, no. 9, pp. 1835C1842, October 2012.

  23. Z. Xiong, M. Dai, F. Sottile, M. A. Spirito, and R. Garello, A cognitive and cooperative tracking approach in wireless networks, in 2013 IEEE International Conference on Communications (ICC), June 2013, pp. 2717C2721.

  24. S. V. de Velde, G. T. F. de Abreu, and H. Steendam, Improved censoring and nlos avoidance for wireless localization in dense networks, IEEE Journal on Selected Areas in Communications, vol. 33, no. 11, pp. 2302C 2312, Nov 2015.

  25. K. Das and H. Wymeersch, Censored cooperative positioning for dense wireless networks, in 2010 IEEE 21st International Symposium on Personal, Indoor and Mobile Radio Communications Workshops, Sept 2010, pp. 262C266.

  26. F. Zhou and G. Wang, Node selection algorithm based on fisher information, EURASIP Journal on Wireless Communications and Networking, Vol. 2016, No. 1, p. 249, 2016.

    Article  Google Scholar 

  27. M. Z. Win, A. Conti, S. Mazuelas, Y. Shen, W. M. Gifford, D. Dardari and M. Chiani, Network localization and navigation via cooperation, IEEE Communications Magazine, Vol. 49, No. 5, p. pp. 56C62, 2011.

    Article  Google Scholar 

  28. H. L. V. Trees, in Detection, Estimation and Modulation Theory, vol. 1, 1968.

  29. I. Reuven and H. Messer, A barankin-type lower bound on the estimation error of a hybrid parameter vector, IEEE Transactions on Information Theory, Vol. 43, No. 3, p. pp. 1084C1093, 1997.

    Article  MATH  Google Scholar 

  30. Y. Shen and M. Z. Win, Fundamental limits of wideband localizationpart i: A general framework, IEEE Transactions on Information Theory, vol. 56, no. 10, pp. 4956C4980, Oct 2010.

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Acknowledgements

This work is supported by the Natural Science Foundation of China under Grant 61671318 and Grant 61401301 and in part by the Tianjin Research Program of Application Foundation and Advanced Technology under Grant 15JCQNJC41900.

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Correspondence to Yongtao Ma.

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Liu, W., Ma, Y. A Novel Method to Select Minimum Neighbors in Cooperative Localization Network. Int J Wireless Inf Networks 26, 1–9 (2019). https://doi.org/10.1007/s10776-018-0419-y

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