GPS-Equipped Wireless Sensor Network Node for High-Accuracy Positioning Applications

  • Bernhard Buchli
  • Felix Sutton
  • Jan Beutel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7158)


This work presents the design, implementation, and end-to-end system concept and integration of a wireless data acquisition system for high-accuracy positioning applications. A wireless network of GPS-equipped sensor nodes, built from low-cost off-the-shelf components, autonomously acquires L1 GPS data for Differential GPS (DGPS) processing of raw satellite information. The differential processing on the backend infrastructure achieves relative position and motion of individual nodes within the network with sub-centimeter accuracy. Leveraging on global GPS time synchronization, network-wide synchronized measurement scheduling, and duty-cycling coupled with power optimized operation and robustness against harsh environmental conditions make the introduced sensor node well suited for monitoring or surveying applications in remote areas. Unattended operation, high spatial and temporal coverage and low cost distinguish this approach from traditional, very costly and time consuming approaches. The prototype data acquisition system based on a low-power mote equipped with a commercially available GPS module has been successfully implemented and validated in a testbed setting.


Wireless Sensor Networks GPS Positioning Geodesy Monitoring 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aberer, K., Hauswirth, M., Salehi, A.: Zero-programming sensor network deployment. In: In Next Generation Service Platforms for Future Mobile Systems, SPMS (2007)Google Scholar
  2. 2.
    Aguado, L., et al.: A low-cost, low-power Galileo/GPS positioning system for monitoring landslides. In: Navitec (October 2006)Google Scholar
  3. 3.
    Astronomical Institute, University of Bern, Bernese GPS software version 5.0 (January 2007) (accessed August 01, 2011)Google Scholar
  4. 4.
    Beran, T., et al.: High-accuracy point positioning with low-cost GPS receivers: how good can it get? In: ION GNSS (2005)Google Scholar
  5. 5.
    Beutel, J., et al.: PermaDAQ: A scientific instrument for precision sensing and data recovery under extreme conditions. In: Proc. 8th ACM/IEEE Int’l Conf. on Information Processing in Sensor Networks (IPSN/SPOTS 2009), pp. 265–276. ACM (2009)Google Scholar
  6. 6.
    Beutel, J., Buchli, B., Ferrari, F., Keller, M., Zimmerling, M., Thiele, L.: X-sense: Sensing in extreme environments. In: Design, Automation Test in Europe Conference Exhibition (DATE), pp. 1–6 (March 2011)Google Scholar
  7. 7.
    Buchli, B., et al.: Demo abstract: Feature-rich platform for WSN design space exploration. In: 10th International Conference on Information Processing in Sensor Networks (IPSN), pp. 115–116 (April 2011)Google Scholar
  8. 8.
    Burri, N., von Rickenbach, P., Wattenhofer, R.: Dozer: Ultra-low power data gathering in sensor networks. In: 6th International Symposium on Information Processing in Sensor Networks, IPSN 2007, pp. 450–459. ACM (April 2010), doi:10.1109/IPSN.2007.4379705Google Scholar
  9. 9.
    Carter, W., Shrestha, R., Slatton, K.: Geodetic laser scanning. Physics Today 60(12), 41–47 (2004)CrossRefGoogle Scholar
  10. 10.
    Choy, S.: An investigation into the accuracy of single frequency precise point positioning (PPP). PhD Thesis. School of Mathematical and Geospatial Sciences, RMIT University (2009)Google Scholar
  11. 11.
    Crozier, M.: Deciphering the effect of climate change on landslide activity: A review. Geomorphology 124(3-4), 260–267 (2010), doi:10.1016/j.geomorph.2010.04.009CrossRefGoogle Scholar
  12. 12.
    D’Amico, S., Montenbruck, O.: Differential GPS: An enabling technology for formation flying satellites. In: Sandau, R., Roeser, H.-P., Valenzuela, A. (eds.) Small Satellite Missions for Earth Observation, pp. 457–465. Springer, Heidelberg (2010), doi:10.1007/978-3-642-03501-2_43CrossRefGoogle Scholar
  13. 13.
    Hasler, A.: Thermal conditions and kinematics of steep bedrock permafrost. PhD Thesis. Department of Geography, University of Zurich (2011)Google Scholar
  14. 14.
    Jurdak, R., et al.: Adaptive GPS duty cycling and radio ranging for energy-efficient localization. In: Proc. of the 8th ACM Conference on Embedded Networked Sensor Systems (Sensys), pp. 57–70. ACM (November 2010), doi:10.1145/1869983.1869990Google Scholar
  15. 15.
    Keller, M., et al.: Comparative performance analysis of the permadozer protocol in diverse deployments. In: Proc. of the Sixth IEEE International Workshop on Practical Issues in Building Sensor Network Applications (SenseApp 2011), pp. 969–977. IEEE, Bonn (2011)Google Scholar
  16. 16.
    Levis, P., et al.: TinyOS: An operating system for sensor networks. In: Ambient Intelligence. Springer, Heidelberg (2004)Google Scholar
  17. 17.
    Limpach, P., Grimm, D.: Rock glacier monitoring with low-cost GPS receivers. In: Abstract Volume 7th Swiss Geoscience Meeting (November 2009)Google Scholar
  18. 18.
    Lucieer, A., Robinson, S., Turner, D.: Using an unmanned aerial vehicle (UAV) for ultra-high resolution mapping of Antarctic moss beds. In: Proc. of the 15th Australasian Remote Sensing & Photogrammetry Conference (September 2010)Google Scholar
  19. 19.
    Martinez, K., Ong, R., Hart, J.: Glacsweb: a sensor network for hostile environments. In: First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, IEEE SECON 2004, pp. 81–87 (October 2004), doi:10.1109/SAHCN.2004.1381905Google Scholar
  20. 20.
    Ravanel, L., Deline, P.: Climate influence on rockfalls in high-alpine steep rockwalls: The north side of the Aiguilles de Chamonix (Mont Blanc massif) since the end of the ’Little Ice Age’. The Holocene 21(2), 357–365 (2010)CrossRefGoogle Scholar
  21. 21.
    Schüler, T., Diessongo, H., Poku-Gyamfi, Y.: Precise ionosphere-free single-frequency GNSS positioning. GPS Solutions 15, 139–147 (2011), doi:10.1007/s10291-010-0177-5CrossRefGoogle Scholar
  22. 22.
    Squarzoni, C., Delacourt, C., Allemand, P.: Differential single-frequency GPS monitoring of the la valette landslide (french alps). Engineering Geology 79(3-4), 215–229 (2005)CrossRefGoogle Scholar
  23. 23.
    Stoleru, R., He, T., Stankovic, J.: Walking GPS: a practical solution for localization in manually deployed wireless sensor networks. In: 29th Annual IEEE International Conference on Local Computer Networks, pp. 480–489 (November 2004), doi:10.1109/LCN.2004.136Google Scholar
  24. 24.
    u-blox AG, u-blox 6 receiver description including protocol specification, (accessed August 01, 2011)
  25. 25.
    U.S. Coast Guard Navigation Center, NAVSTAR GPS user equipment introduction (September 1996) (accessed August 01, 2011)Google Scholar
  26. 26.
    Werner-Allen, G., et al.: Fidelity and yield in a volcano monitoring sensor network. In: Proc. of the 7th Symposium on Operating Systems Design and Implementation, OSDI 2006, pp. 381–396. USENIX Association, Berkeley (2006)Google Scholar
  27. 27.
    Wirz, V., et al.: Temporal characteristics of different cryosphere-related slope movements in high mountains. In: Proc. 2nd World Landslide Forum. Springer, Heidelberg (2011)Google Scholar
  28. 28.
    Wright, T., et al.: InSAR observations of low slip rates on the major faults of western Tibet. Science 305(5681), 236–239 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bernhard Buchli
    • 1
  • Felix Sutton
    • 1
  • Jan Beutel
    • 1
  1. 1.Computer Engineering and Networks LaboratoryETH ZurichZurichSwitzerland

Personalised recommendations