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    A widely linear multichannel Wiener Filter for wind prediction

    Dowell, J. and Weiss, S. and Infield, D. and Chandna, Swati (2014) A widely linear multichannel Wiener Filter for wind prediction. 2014 IEEE Workshop on Statistical Signal Processing (SSP) , pp. 29-32. ISSN 2373-0803.

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    Abstract

    The desire to improve short-term predictions of wind speed and direction has motivated the development of a spatial covariance-based predictor in a complex valued multichannel structure. Wind speed and direction are modeled as the magnitude and phase of complex time series and measurements from multiple geographic locations are embedded in a complex vector which is then used as input to a multichannel Wiener prediction filter. Building on a C-linear cyclo-stationary predictor, a new widely linear filter is developed and tested on hourly mean wind speed and direction measurements made at 13 locations in the UK over 6 years. The new predictor shows a reduction in mean squared error at all locations. Furthermore it is found that the scale of that reduction strongly depends on conditions local to the measurement site.

    Metadata

    Item Type: Article
    Additional Information: (c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Print ISSN: 2373-0803.
    Keyword(s) / Subject(s): Widely linear processing, prediction, complex data, Wiener filter
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Economics, Mathematics and Statistics
    Depositing User: Dr Swati Chandna
    Date Deposited: 22 Jan 2019 10:36
    Last Modified: 04 Feb 2019 09:50
    URI: http://eprints.bbk.ac.uk/id/eprint/25913

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