• DocumentCode
    1114380
  • Title

    Estimation and Optimal Configurations for Localization Using Cooperative UAVs

  • Author

    Purvis, Keith B. ; Åström, Karl J. ; Khammash, Mustafa

  • Author_Institution
    Toyon Res. Corp., Goleta, CA
  • Volume
    16
  • Issue
    5
  • fYear
    2008
  • Firstpage
    947
  • Lastpage
    958
  • Abstract
    The time-difference of arrival techniques are adapted to locate networked enemy radars using a cooperative team of unmanned aerial vehicles. The team is engaged in deceiving the radars, which limits where they can fly and requires accurate radar positions to be known. Two time-differences of radar pulse arrivals at two vehicle pairs are used to localize one of the radars. An explicit solution for the radar position in polar coordinates is developed. The solution is first used for position estimation given ldquonoisyrdquo measurements, which shows that the vehicle trajectories significantly affect estimation accuracy. Analyzing the explicit solution leads to the angle rule, which gives the optimal vehicle configuration for the angle estimate. Analyzing the fisher Information matrix leads to the coordinate rule, which gives a different optimal configuration for the position estimate. A linearized time-varying model is also formulated and an extended Kalman filter applied. This estimation scheme is compared with the earlier one, with the second showing overall improvement in reducing the variance of the estimate.
  • Keywords
    Kalman filters; aircraft; cooperative systems; mobile robots; multi-robot systems; nonlinear filters; remotely operated vehicles; spaceborne radar; time-of-arrival estimation; time-varying systems; Fisher information matrix; cooperative UAV; cooperative team; coordinate rule; extended Kalman filter; linearized time-varying model; networked enemy radars; optimal vehicle configuration; position estimation; radar positions; radar pulse arrivals; the angle rule; time-difference of arrival techniques; unmanned aerial vehicles; Electronic warfare; Fisher Information Matrix; Kalman filtering; localization; optimal configuration; position estimation; unmanned aerial vehicles (UAVs);
  • fLanguage
    English
  • Journal_Title
    Control Systems Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6536
  • Type

    jour

  • DOI
    10.1109/TCST.2007.916348
  • Filename
    4476759