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

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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.

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Authors and Affiliations

  1. Laboratoire Heudiasyc UMR CNRS 6599, Université de Technologie de Compiègne, 60200, Compiègne, France

    José-Luis Rullán-Lara & Rogelio Lozano

  2. Laboratoire Franco-Mexicain d’Informatique et Automatique, LAFMIA UMI 3175 CNRS-CINVESTAV, Mexico, Mexico

    Sergio Salazar & Rogelio Lozano

Authors
  1. José-Luis Rullán-Lara
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  2. Sergio Salazar
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  3. Rogelio Lozano
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Correspondence to José-Luis Rullán-Lara.

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Rullán-Lara, JL., Salazar, S. & Lozano, R. Real-time localization of an UAV using Kalman filter and a Wireless Sensor Network. J Intell Robot Syst 65, 283–293 (2012). https://doi.org/10.1007/s10846-011-9599-8

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  • DOI: https://doi.org/10.1007/s10846-011-9599-8

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