Real-time localization of an UAV using Kalman filter and a Wireless Sensor Network

  • Authors:
  • José-Luis Rullán-Lara;Sergio Salazar;Rogelio Lozano

  • Affiliations:
  • Laboratoire Heudiasyc UMR CNRS 6599, Université de Technologie de Compiègne, Compiègne, France 60200;Laboratoire Franco-Mexicain d'Informatique et Automatique, LAFMIA UMI 3175 CNRS-CINVESTAV, Mexico, Mexico;Laboratoire Heudiasyc UMR CNRS 6599, Université de Technologie de Compiègne, Compiègne, France 60200 and Laboratoire Franco-Mexicain d'Informatique et Automatique, LAFMIA UMI 3175 C ...

  • Venue:
  • Journal of Intelligent and Robotic Systems
  • Year:
  • 2012

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Abstract

A real-time localization algorithm is presented in this paper. The algorithm presented here uses an Extended Kalman Filter and is based on time difference of arrivals (TDOA) measurements of radio signal. The position and velocity of an Unmanned Aerial Vehicle (UAV) are successfully estimated in closed-loop in real-time in both hover and path following flights. Relatively small position errors obtained from the experiments, proves a good performance of the proposed algorithm.