Optimal Path Planning for Two Unmanned Aerial Vehicles in DRSS Localization

  • Seyyed Ali Asghar Shahidian
  • Hadi Soltanizadeh
Regular Papers Robot and Applications


Optimal path planning for three or more unmanned aerial vehicles (UAVs) in radio source localization has been studied extensively; but path planning for two UAVs in signal strength based localization is still a challenge. This paper investigates the autonomous path planning for a pair of UAVs equipped with received signal strength (RSS) sensors applying optimum experimental design criteria based on the fisher information matrix (FIM). The control strategy steers the UAVs along the paths that minimize the emitter location uncertainty. Since there is one differential received signal strength (DRSS) measurement (two RSS sensors) in each time step, the emitter location uncertainty is infinite for a single measurement and the FIM is singular. The FIM is approximated at successive waypoints using the estimated location of the emitter produced by the extended kalman filter (EKF). The objective of this paper is to propose path planning approaches for minimum number of UAVs in DRSS-based localization based on different optimum criteria including D-, E-, A-optimality and sensitivity. Each criterion is related to a different characteristic of the estimation uncertainty ellipsoid and consequently generates different trajectories. The proposed steering algorithms are evaluated through extensive simulations.


Differential received signal strength extended Kalman filters fisher Information path planning unmanned aerial vehicles 


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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Seyyed Ali Asghar Shahidian
    • 1
  • Hadi Soltanizadeh
    • 2
  1. 1.Young Researchers and Elite Club, Robatkarim BranchIslamic Azad UniversityRobatkarimIran
  2. 2.Department of Electrical and Computer EngineeringSemnan UniversitySemnanIran

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