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Cooperative Estimation for Coordinated Target Tracking in a Cluttered Environment

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Abstract

The purpose of the work in this paper is to gain insight into several fundamental questions that arise whenever a distributed multiple-vehicle control system is endowed with communication capabilities. These fundamental questions include: what data should each vehicle share?, how frequently should communication take place?, and what benefit does communication provide? These questions are evaluated with respect to a target tracking task in which multiple pursuit vehicles estimate the state of a target vehicle. This task has three main components: communication, estimation, and control. Communication takes place on a broadcast network, estimation is achieved with an Unscented Kalman Filters, and the controller is behavior-based. Simulation results show that communication always improves distributed estimate results. Which information to transmit depends on available bandwidth, and more frequent communication generally yields better estimates. Simulation results also show how coordinated control can be beneficial to target tracking in a cluttered environment.

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References

  1. Bar-Shalom Y, Li XR (1995) Multitarget-multisensor tracking: principles and techniques. Yaakov Bar-Shalom, Storrs

    Google Scholar 

  2. Campbell ME, Whitacre WW (2007) Cooperative tracking using vision measurements on seascan UAVs. IEEE Trans Control Syst Technol 15(4):613–626

    Article  Google Scholar 

  3. Chang KC, Saha RK, Bar-Shalom Y (1997) On optimal track-to-track fusion. IEEE Trans Aerosp Electron Syst 33(4):1271–1276

    Article  Google Scholar 

  4. Chen H, Bar-Shalom Y (2006) Track fusion with legacy track sources. In: 9th international conference on information fusion, 2006. ICIF’06, pp 1–8

  5. Eickstedt DP, Benjamin MR (2006) Cooperative target tracking in a distributed autonomous sensor network. In: OCEANS 2006, pp 1–6, September

  6. Justh EW, Krishnaprasad PS (2004) Equilibria and steering laws for planar formations. Syst Control Lett 52:25–38

    Article  MATH  MathSciNet  Google Scholar 

  7. Klein DJ, Morgansen KA (2006) Controlled collective motion for trajectory tracking. In: Proc of the 2006 American control conference, Minneapolis, MN, June

  8. La Scala BF, Farina A (2002) Choosing a track association method. Inf Fusion 3(2):119–133

    Article  Google Scholar 

  9. Nettleton EW, Durrant-Whyte H (2001) Delayed and asequent data in decentralised sensing networks. In: Proc SPIE Conf, vol 4571, pp 255–266

  10. Olfati-Saber R (2007) Distributed kalman filtering for sensor networks. In: Proc. of the 46th conference on decision and control, December

  11. Simon D (2006) Optimal state estimation: Kalman, H infinity, and nonlinear approaches. Wiley-Interscience, New York

    Google Scholar 

  12. Triplett BI, Klein DJ, Morgansen KA (2007) Distributed estimation for coordinated target tracking in a cluttered environment. In: Proc. of Robocomm, Athens, Greece, October

  13. Wheeler M, Schrick B, Whitacre W, Campbell M, Rysdyk R, Wise R (2006) Cooperative tracking of moving targets by a team of autonomous uavs. In: 25th digital avionics systems conference, 2006 IEEE/AIAA, pp 1–9, October

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Acknowledgements

This work was supported by NSF grant CMS-0238461 and AFOSR grants FA9550-05-1-0430 and FA9550-07-1-0528.

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Authors and Affiliations

  1. Department of Aeronautics and Astronautics, University of Washington, Seattle, WA, 98195-2400, USA

    Benjamin I. Triplett, Daniel J. Klein & Kristi A. Morgansen

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  1. Benjamin I. Triplett
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  2. Daniel J. Klein
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  3. Kristi A. Morgansen
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Correspondence to Benjamin I. Triplett.

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Triplett, B.I., Klein, D.J. & Morgansen, K.A. Cooperative Estimation for Coordinated Target Tracking in a Cluttered Environment. Mobile Netw Appl 14, 336–349 (2009). https://doi.org/10.1007/s11036-008-0151-4

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