Nothing Special   »   [go: up one dir, main page]

Skip to main content

Vision Based Mobile Target Geo-localization and Target Discrimination Using Bayes Detection Theory

  • Conference paper
Distributed Autonomous Robotic Systems

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 104))

Abstract

In this paper, we develop a technique to discriminate ground moving targets when viewed from cameras mounted on different fixed wing unmanned aerial vehicles (UAVs). First, we develop a extended kalman filter (EKF) technique to estimate position and velocity of ground moving targets using images taken from cameras mounted on UAVs. Next, we use Bayesian detection theory to derive a log likelihood ratio test to determine if the estimates of moving targets computed at two different UAVs belong to a same target or to two different targets. We show the efficacy of the log likelihood ratio test using several simulation results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Quigley, M., Goodrich, M.A., Griffiths, S., Eldredge, A., Beard, R.W.: Target acquisition, localization, and surveillance using a fixed-wing mini-UAV and gimbaled camera. In: Proc. IEEE Int. Conf. Robotics and Automation ICRA 2005, pp. 2600–2605 (2005)

    Google Scholar 

  2. Ayyagari, A., Harrang, J.P., Ray, S.: Airborne information and reconnaissance network. In: Proc. IEEE Military Communications Conf. MILCOM 1996, vol. 1, pp. 230–234 (1996)

    Google Scholar 

  3. Beard, R.W., McLain, T.W.: Multiple UAV cooperative search under collision avoidance and limited range communication constraints. In: Proc. 42nd IEEE Conference on Decision and Control, December 9-12, vol. 1, pp. 25–30 (2003)

    Google Scholar 

  4. Casbeer, D.W., Beard, R.W., McLain, T.W., Li, S.-M., Mehra, R.K.: Forest fire monitoring with multiple small UAVs. In: Proc. American Control Conf the 2005, pp. 3530–3535 (2005)

    Google Scholar 

  5. Sujit, P.B., Kingston, D., Beard, R.: Cooperative forest fire monitoring using multiple UAVs. In: Proc. 46th IEEE Conf. Decision and Control, pp. 4875–4880 (2007)

    Google Scholar 

  6. Pachter, M., Ceccarelli, N., Chandler, P.R.: Vision-based target geo-location using camera equipped MAVs. In: Proc. 46th IEEE Conf. Decision and Control, pp. 2333–2338 (2007)

    Google Scholar 

  7. Barber, D.B., Redding, J.D., McLain, T.W., Beard, R.W., Taylor, C.N.: Vision-based target geo-location using a fixed-wing miniature air vehicle. Journal of Intelligent and Robotic Systems 47(4) (December 2006)

    Google Scholar 

  8. Frew, E.W.: Sensitivity of cooperative target geolocalization to orbit coordination. Journal of Guidance, Control, and Dynamics 31(4) (August 2008)

    Google Scholar 

  9. Ross, J.A., Geiger, B.R., Sinsley, G.L., Horn, J.F., Long, L.N., Niessner, A.F.: Vision-based target geolocation and optimal surveillance on an unmanned aerial vehicle. In: AIAA, Guidance, Navigation, and Control Confrence, Honolulu, Hawaii (August 2008)

    Google Scholar 

  10. Olfati-Saber, R.: Distributed kalman filter with embedded consensus filters. In: 44th IEEE Conference on Proc. and 2005 European Control Conference Decision and Control CDC-ECC 2005, December 12-15, pp. 8179–8184 (2005)

    Google Scholar 

  11. Niehsen, W.: Information fusion based on fast covariance intersection filtering. In: Proc. Fifth International Conference on Information Fusion, July 8-11, vol. 2, pp. 901–904 (2002)

    Google Scholar 

  12. Casbeer, D.W., Beard, R.: Distributed information filtering using consensus filters. In: American Control Conference on Proc. ACC 2009, June 10-12 (2009)

    Google Scholar 

  13. Kirubarajan, T., Yakov, B.-S.: Probabilistic Data Association Techniques for Target Tracking in Clutter. Proceedings of the IEEE 92(3), 536–537 (2004)

    Google Scholar 

  14. Leonard, J.J., Durrant-Whyte, H.F., Cox, I.J.: Dynamic map building for an autonomous mobile robot. The International Journal of Robotics Research 11(4), 286–298 (1992), http://ijr.sagepub.com/content/11/4/286.abstract

    Article  Google Scholar 

  15. Yaakov, B.-S., Thomas, E.F.: Tracking and Data Association. Academic, NewYork (1988)

    MATH  Google Scholar 

  16. Gil, A., Reinoso, O., Mozos, O., Stachnissi, C., Burgard, W.: Improving data association in vision-based SLAM. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (2006)

    Google Scholar 

  17. Beard, R., McLain, T.W.: Small Unmanned Aircraft: Theory and practice. Princeton University Press (2011)

    Google Scholar 

  18. Moon, T.K., Stirling, W.C.: Mathematical Methods and Algorithms in Signal Processing. Prentice-Hall, Upper Saddle River (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rajnikant Sharma .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sharma, R., Yoder, J., Kwon, H., Pack, D. (2014). Vision Based Mobile Target Geo-localization and Target Discrimination Using Bayes Detection Theory. In: Ani Hsieh, M., Chirikjian, G. (eds) Distributed Autonomous Robotic Systems. Springer Tracts in Advanced Robotics, vol 104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55146-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-55146-8_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-55145-1

  • Online ISBN: 978-3-642-55146-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics