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Optimal Tracking of Multiple Targets Using UAVs

  • David Hay
  • Shahrzad ShirazipourazadEmail author
  • Arunabha Sen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8881)

Abstract

Target tracking problems have been studied fairly extensively by researchers in the last few years. However, the problem of continuous tracking of all mobile targets using the fewest number of mobile trackers, even when the trajectories of all the targets are known in advance, has received very little attention. In this paper we study this problem, where the goal is to find the fewest number of trackers needed to track all the targets for the entire period of observation. Specifically, given a set of \(n\) targets moving in \(n\) different (known) trajectories in a two (or three) dimensional space, our objective is to find the fewest number of velocity-bounded UAVs (mobile sensors, trackers) and their trajectories, so that all the targets are tracked during the entire period of observation. We also study two other versions of the problem where not only the number of trackers but also the time during which the trackers are active is also taken into account. We formulate these problems as network flow problems and propose algorithms for their solution. We evaluate the performance of our algorithms through simulation and study the impact of parameters such as the speed and sensing range of the trackers.

Notes

Acknowledgments

This research is supported in part by grants from the U.S. Defense Threat Reduction Agency under grant number HDTRA1-09-1-0032, the U.S. Air Force Office of Scientific Research under grant number FA9550-09-1-0120, and the Israeli Centers of Research Excellence (I-CORE) program (Center No. 4/11).

References

  1. 1.
    Zorbas, D., Razafindralambo, T., Luigi, D.P.P., Guerriero, F.: Energy efficient mobile target tracking using flying drones. Procedia Comput. Sci. 19, 80–87 (2013)CrossRefGoogle Scholar
  2. 2.
    Zhan, P., Casbeer, D., Swindlehurst, A.: A centralized control algorithm for target tracking with uavs. In: Conference Record of the Thirty-Ninth Asilomar Conference on Signals, Systems and Computers, pp. 1148–1152, October 2005Google Scholar
  3. 3.
    Wheeler, M., Schrick, B., Whitacre, W., Campbell, M., Rysdyk, R., Wise, R.: Cooperative tracking of moving targets by a team of autonomous uavs. In: IEEE/AIAA 25th Digital Avionics Systems Conference, pp. 1–9, October 2006Google Scholar
  4. 4.
    Nitinawarat, S., Atia, G., Veeravalli, V.: Efficient target tracking using mobile sensors. In: 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 405–408, December 2011Google Scholar
  5. 5.
    Xu, E., Ding, Z., Dasgupta, S.: Target tracking and mobile sensor navigation in wireless sensor networks. IEEE Trans. Mob. Comput. 12(1), 177–186 (2013)CrossRefGoogle Scholar
  6. 6.
    Zou, Y., Chakrabarty, K.: Distributed mobility management for target tracking in mobile sensor networks. IEEE Trans. Mobile Comput. 6(8), 872–887 (2007)CrossRefGoogle Scholar
  7. 7.
    Naderan, M., Dehghan, M., Pedram, H.: Mobile object tracking techniques in wireless sensor networks. In: International Conference on Ultra Modern Telecommunications Workshops, ICUMT ’09, pp. 1–8, October 2009Google Scholar
  8. 8.
    Adamey, E., Ozguner, U.: A decentralized approach for multi-UAV multitarget tracking and surveillance. In: Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, vol. 8389. May 2012Google Scholar
  9. 9.
    Srinivas, A., Zussman, G., Modiano, E.: Construction and maintenance of wireless mobile backbone networks. IEEE/ACM Trans. Networking 17(1), 239–252 (2009)CrossRefGoogle Scholar
  10. 10.
    Radhakrishnan, G., Saripalli, S.: Target tracking with communication constraints: An aerial perspective. In: IEEE International Workshop on Robotic and Sensors Environments (ROSE), pp. 1–6, October 2010Google Scholar
  11. 11.
    Fowler, R.J., Paterson, M.S., Tanimoto, S.L.: Optimal packing and covering in the plane are np-complete. Inf. Process. Lett. 12(3), 133–137 (1981)CrossRefzbMATHMathSciNetGoogle Scholar
  12. 12.
    Even, S.: Graph Algorithms. W. H. Freeman & Co., New York (1979)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • David Hay
    • 1
  • Shahrzad Shirazipourazad
    • 2
    Email author
  • Arunabha Sen
    • 2
  1. 1.School of Computer Science and EngineeringHebrew UniversityJerusalemIsrael
  2. 2.School of Computing, Informatics and Decision System EngineeringArizona State UniversityTempeUSA

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