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11 - Computer Science and Informatics

University of the West of Scotland

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Article title

UAV Position Estimation and Collision Avoidance using the Extended Kalman Filter

Type

D - Journal article

DOI

10.1109/TVT.2013.2243480

Title of journal

IEEE Transactions on Vehicular Technology

Article number

Volume number

Issue number

First page of article

ISSN of journal

1939-9359

Year of publication

2013

URL

Number of additional authors

Additional information

<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.

Interdisciplinary

Cross-referral requested

Research group

None

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract