inTrack: High Precision Tracking of Mobile Sensor Nodes

  • Branislav Kusý
  • György Balogh
  • János Sallai
  • Ákos Lédeczi
  • Miklós Maróti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4373)

Abstract

Radio-interferometric ranging is a novel technique that allows for fine-grained node localization in networks of inexpensive COTS nodes. In this paper, we show that the approach can also be applied to precision tracking of mobile sensor nodes. We introduce inTrack, a cooperative tracking system based on radio-interferometry that features high accuracy, long range and low-power operation. The system utilizes a set of nodes placed at known locations to track a mobile sensor. We analyze how target speed and measurement errors affect the accuracy of the computed locations. To demonstrate the feasibility of our approach, we describe our prototype implementation using Berkeley motes. We evaluate the system using data from both simulations and field tests.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Maróti, M., et al.: Radio-interferometric geolocation. In: Proc. ACM 3rd Conference on Embedded Networked Sensor Systems (SenSys), San Diego, CA, USA, ACM Press, New York (2005)Google Scholar
  2. 2.
    Kusý, B., Lédeczi, A., Maróti, M., Meertens, L.: Node-density independent localization. In: Proc. of 5th Int’l Symposium on Information Processing in Sensor Networks (IPSN SPOTS), Nashville, TN, USA (2006)Google Scholar
  3. 3.
    Lédeczi, A., et al.: Countersniper System for Urban Warfare. ACM Transactions on Sensor Networks 1, 153–177 (2005)CrossRefGoogle Scholar
  4. 4.
    Addlesee, M., et al.: Implementing a Sentient Computing System. Computer 34(8), 50–56 (2001)CrossRefGoogle Scholar
  5. 5.
    Bulusu, N., Heidemann, J., Estrin, D.: GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications 7(5), 28–34 (2000)CrossRefGoogle Scholar
  6. 6.
    Hazas, M., Hopper, A.: Broadband Ultrasonic Location Systems for Improved Indoor Positioning. IEEE Transactions on Mobile Computing 5(5), 536–547 (2006)CrossRefGoogle Scholar
  7. 7.
    Hightower, J., Borriello, G.: Location Systems for Ubiquitous Computing. Computer 34(8), 57–66 (2001)CrossRefGoogle Scholar
  8. 8.
    Hightower, J., Want, R., Borriello, G.: SpotON: An indoor 3D location sensing technology based on RF signal strength. UW CSE 00-02-02, University of Washington, Department of Computer Science and Engineering, Seattle, WA (Feb. 2000)Google Scholar
  9. 9.
    Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., Pister, K.: System architecture directions for networked sensors. In: Proc. of ASPLOS 2000, Cambridge, MA (2000)Google Scholar
  10. 10.
    Hofmann-Wellenhof, B., Lichtenegger, H., Collins, J.: Global Positioning System: Theory and Practice, 4th edn. Springer, Heidelberg (1997)Google Scholar
  11. 11.
    Moore, D., Leonard, J., Rus, D., Teller, S.: Robust distributed network localization with noisy range measurements. In: Proceedings of ACM Sensys, Nov., ACM Press, New York (2004)Google Scholar
  12. 12.
    Pathirana, P., Bulusu, N., Jha, S., Savkin, A.: Node localization using mobile robots in delay-tolerant sensor networks. IEEE Transactions on Mobile Computing 4(4) (2005)Google Scholar
  13. 13.
    Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: Cricket Location-Support System. In: Proc. Sixth Int’l Conf. Mobile Computing and Networking (MobiCom) (2000)Google Scholar
  14. 14.
    Savvides, A., Han, C., Srivastava, M.: Dynamic finegrained localization in ad-hoc networks of sensors. In: 7th ACM Int. Conf. on Mobile Computing and Networking (Mobicom), Rome, Italy, July 2001, pp. 166–179. ACM Press, New York (2001)Google Scholar
  15. 15.
    Taylor, C., Rahimi, A., Bachrach, J., Shrobe, H., Grue, A.: Simultaneous Localization, Calibration and Tracking in an Ad Hoc Sensor Network. In: Proc. 5th Int’l Symposium on Information Processing in Sensor Networks (IPSN), Nashville, TN, USA (2006)Google Scholar
  16. 16.
    Dutta, P., Grimmer, M., Arora, A., Bibyk, S., Culler, D.: Design of a wireless sensor network platform for detecting rare, random, and ephemeral events. In: Proc. of 4th Int’l Conference on Information Processing in Sensor Networks (IPSN SPOTS), April (2005)Google Scholar
  17. 17.
    Chipcon: CC1000 Product Information (2004 ), http://www.chipcon.com
  18. 18.
    Hu, C., Xu, S., Yang, X.: A Review on Interval Computation – Software and Applications. Int. J. of Computational and Numerical Analysis and Applications, 1(2), 149–162 (2002)MathSciNetMATHGoogle Scholar
  19. 19.
    Kusy, B., Dutta, P., Levis, P., Maroti, M., Ledeczi, A., Culler, D.: Elapsed Time on Arrival: A simple and versatile primitive for canonical time synchronization services. International Journal of Ad Hoc and Ubiquitous Computing (January 1, 2006)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Branislav Kusý
    • 1
  • György Balogh
    • 1
  • János Sallai
    • 1
  • Ákos Lédeczi
    • 1
  • Miklós Maróti
    • 2
  1. 1.Institute for Software Integrated Systems, Vanderbilt University, Nashville, TNUSA
  2. 2.Department of Mathematics, University of SzegedHungary

Personalised recommendations