BIROn - Birkbeck Institutional Research Online

    Error propagation analysis for a Static Convergent Beam Triple LIDAR

    Holtom, T.C. and Brooms, Anthony C. (2019) Error propagation analysis for a Static Convergent Beam Triple LIDAR. Technical Report. Birkbeck College, University of London, London, UK, London, UK.

    [img]
    Preview
    Text
    25809a.pdf - Published Version of Record

    Download (1MB) | Preview

    Abstract

    We consider the issue of uncertainty propagation and quantification for the converging triplebeam LIDAR technology used for measuring wind velocity passing through a fixed point in space. Converging triple-beam LIDAR employs the use of three non-parallel, non-coplanar, laser beams which are directed from a fixed platform, typically at ground level, that extend to meet at the point at which measurement of velocity is sought. Coordinate values of the velocity are ascertained with respect to unit vectors along the lines of sight of the laser beams (Doppler vectors), which are then resolved in order determine the velocity in terms of Cartesian coordinates (i.e. with respect to the standard basis). However, if there is any discrepancy between the recorded values of the coordinates with respect to the Doppler unit vectors and/or the perceived angle settings for such vectors with what they really should be, however small, then this will lead to errors in the reconstructed Cartesian coordinates. The aim of this paper is to quantify the potential size of this error by consideration of its variance within each component of the reconstructed velocity vector through the use of the error propagation formula.

    Metadata

    Item Type: Monograph (Technical Report)
    Additional Information: Birkbeck Mathematics Preprint Series #41
    Keyword(s) / Subject(s): WIND TURBINES, WIND VELOCITY FIELD, CONVERGING BEAM LIDAR, DOPPLER LIDAR, DOPPLER VECTORS, VELOCITY RECONSTRUCTION, MEASUREMENT ERROR, FORWARD ERROR PROPAGATION, ERROR PROPAGATION FORMULA
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: Anthony Brooms
    Date Deposited: 18 Jan 2019 08:07
    Last Modified: 09 Aug 2023 12:45
    URI: https://eprints.bbk.ac.uk/id/eprint/25809

    Statistics

    Activity Overview
    6 month trend
    270Downloads
    6 month trend
    467Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item
    Edit/View Item