Output details
11 - Computer Science and Informatics
University of the West of Scotland
UAV Position Estimation and Collision Avoidance using the Extended Kalman Filter
<02> This paper proposes an innovative technique to improve the precision of using radio frequency signal to estimate the positions of unmanned aerial vehicles (UAV) and build a collision avoidance strategy. The achieved result is one of the major contributions to the EPSRC funded projects (EP/F06358X/1) (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/F06358X/1) and (EP/F064179/1) (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/F064179/1). Part of the results with Oxford University was also published in another paper (http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6477815, one of the two flagship conferences of the IEEE Communications Society). This paper is also presented in an invited keynote speech in TU Dortmund in Germany and in Oxford University.