Robust speed measurements with standard wireless devices

Robust speed measurements with standard wireless devices

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Wireless Sensor Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Speed measurements are crucial for controlling traffic and in supporting automation of industrial processes. The speed of moving objects is typically measured from a stationary position using time-of-flight or the Doppler effect. Existing approaches require either relatively bulky physical devices or complex signal processing. The authors propose a new method for measuring the speed of (metal) objects moving on a fixed track. The authors’ method is applicable, e.g. to cars on a road, trains on rails, or goods sliding on a conveyor belt. The method relies on the constructive and destructive interference patterns created by the reflections from the moving target. Speed is determined by measuring the signal strength of received messages as perceived by standard wireless devices. The method requires only minimal signal processing and only two commodity wireless transceivers, which are independent of the moving target. The advantages of their system compared to other technologies are reduced size, reduced cost, and in some scenarios robustness.


    1. 1)
      • 1. Friedlander, B.: ‘Accuracy of source localization using multipath delays’, IEEE Trans. Aerosp. Electron. Syst., 1988, 24, (4), pp. 346359.
    2. 2)
      • 2. Lo, K.W., Ferguson, B.G., Gao, Y., et al: ‘Aircraft flight parameter estimation using acoustic multipath delays’, IEEE Trans. Aerosp. Electron. Syst., 2003, 39, (1), pp. 259268.
    3. 3)
      • 3. Cardinali, R., Colone, F., Ferretti, C., et al: ‘Comparison of clutter and multipath cancellation techniques for passive radar’. IEEE Radar Conf., 2007.
    4. 4)
      • 4. White, W.: ‘Low-angle radar tracking in the presence of multipath’, IEEE Trans. Aerosp. Electron. Syst., 1974, (6), pp. 835852.
    5. 5)
      • 5. Roehr, S., Gulden, P., Vossiek, M.: ‘Precise distance and velocity measurement for real time locating in multipath environments using a frequency-modulated continuous-wave secondary radar approach’, IEEE Trans. Microw. Theory Tech., 2008, 56, (10), pp. 23292339.
    6. 6)
      • 6. Martín, S.R., Genescá, M., Romeu, J., et al: ‘Aircraft tracking by means of the acoustical Doppler effect’, Aerosp. Sci. Technol., 2013, 28, (1), pp. 305314.
    7. 7)
      • 7. Coutts, S.D.: ‘Passive localization of moving emitters using out-of-plane multipath’, IEEE Trans. Aerosp. Electron. Syst., 2000, 36, (2), pp. 584595.
    8. 8)
      • 8. Hatakeyama, K., Sakata, Y., Hashimoto, T., et al: ‘Detection of buried human body by electromagnetic wave reflection’. Int. Symp. on Electromagnetic Compatibility, 1999, pp. 805817.
    9. 9)
      • 9. Schneider, J., Wattenhofer, R.: ‘Coloring unstructured wireless multi-hop networks’. Proc. of the 28th ACM Symp. on Principles of Distributed Computing, 2009, pp. 210219.
    10. 10)
      • 10. Schneider, J., Wattenhofer, R.: ‘Message position modulation for power saving and increased bandwidth in sensor networks’. 10th Int. Conf. on Information Processing in Sensor Networks (IPSN), 2011, 2011, pp. 149150.
    11. 11)
      • 11. Oberholzer, G., Sommer, P., Wattenhofer, R.: ‘The spiderbat ultrasound positioning system’. Embedded Networked Sensor Systems (SenSys), 2010, pp. 403404.
    12. 12)
      • 12. Zanca, G., Zorzi, F., Zanella, A., et al: ‘Experimental comparison of rssi-based localization algorithms for indoor wireless sensor networks’. Real-World Wireless Sensor Networks (REALWSN), 2008, pp. 15.
    13. 13)
      • 13. Parameswaran, A.T., Husain, M.I., Upadhyaya, S., et al: ‘Is RSSI a reliable parameter in sensor localization algorithms: an experimental study’. Field Failure Data Analysis Workshop (F2DA09), 2009, pp. 510.
    14. 14)
      • 14. Heurtefeux, K., Valois, F.: ‘Is rssi a good choice for localization in wireless sensor network?’. 26th Int. Conf. on Advanced Information Networking and Applications (AINA), 2012, 2012, pp. 732739.
    15. 15)
      • 15. Jin, R., Xu, H., Che, Z., et al: ‘Experimental evaluation of reducing ranging-error based on receive signal strength indication in wireless sensor networks’, IET Wirel. Sens. Syst., 2015, 5, (5), pp. 228234.
    16. 16)
      • 16. Pagano, S., Peirani, S., Valle, M.: ‘Indoor ranging and localisation algorithm based on received signal strength indicator using statistic parameters for wireless sensor networks’, IET Wirel. Sens. Syst., 5, (5), pp. 243249.
    17. 17)
      • 17. Feger, R., Pfeffer, C., Scheiblhofer, W., et al: ‘A 77-ghz cooperative radar system based on multi-channel fmcw stations for local positioning applications’, IEEE Trans. Microw. Theory Tech., 2013, 61, (1), pp. 676684.
    18. 18)
      • 18. Youssef, M., Mah, M., Agrawala, A.K.: ‘Challenges: device-free passive localization for wireless environments’. Mobile Computing and Networking (MOBICOM), 2007, pp. 222229.
    19. 19)
      • 19. Wilson, J., Patwari, N.: ‘Through-wall tracking using variance-based radio tomography networks’. CoRR, 2009, abs/0909.5417.
    20. 20)
      • 20. Seifeldin, M., Saeed, A., Kosba, A.E., et al: ‘Nuzzer: a large-scale device-free passive localization system for wireless environments’, IEEE Trans. Mob. Comput., 2013, 12, (7), pp. 13211334.
    21. 21)
      • 21. Mao, X., Inoue, D., Kato, S., et al: ‘Amplitude-modulated laser radar for range and speed measurement in car applications’, IEEE Trans. Intell. Transp. Syst., 2012, 13, (1), pp. 408413.
    22. 22)
      • 22. Sivaraman, S., Trivedi, M.M.: ‘Looking at vehicles on the road: a survey of vision-based vehicle detection, tracking, behavior analysis’, IEEE Trans. Intell. Transp. Syst., 2013, 14, (4), pp. 17731795.
    23. 23)
      • 23. Rad, A.G., Dehghani, A., Karim, M.R.: ‘Vehicle speed detection in video image sequences using cvs method’, Int. J. Phys. Sci., 2010, 5, (17), pp. 25552563.
    24. 24)
      • 24. Schaffer, B., Kalverkamp, G., Chaabane, M., et al: ‘A cooperative transponder system for improved traffic safety, localizing road users in the 5 GHz band’, Adv. Radio Sci., 2012, 10, (4), pp. 3944.
    25. 25)
      • 25. Schaffer, B., Kalverkamp, G., Biebl, E.: ‘A 2.4 GHz high precision local positioning system based on cooperative roundtrip time of flight ranging’. German Microwave Conf. (GeMIC), 2014, pp. 14.
    26. 26)
      • 26. Kloeden, H., Damak, N., Rasshofer, R.H., et al: ‘Sensor resource management with cooperative sensors for preventive vehicle safety applications’. Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2013 Workshop on, 2013, pp. 16.
    27. 27)
      • 27. Subramaniam, M., Tharmarasa, R., Pelletier, M., et al: ‘Multipath-assisted multitarget tracking using multiframe assignment’. SPIE Optical Engineering + Applications. Int. Society for Optics and Photonics, 2009.
    28. 28)
      • 28. Wang, S.-H., Chang, R.-S., Tsai, S.-L.: ‘Tracking objects using hexagons in sensor networks’, IET Wirel. Sens. Syst., 2012, 2, (4), pp. 309317.
    29. 29)
      • 29. Caracas, A., Kramp, T., Baentsch, M., et al: ‘Mote runner: a multi-language virtual machine for small embedded devices’. Sensor Technologies and Applications (SENSORCOMM), 2009, pp. 117125.

Related content

This is a required field
Please enter a valid email address