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    Canonical correlations for target detection in a passive radar network

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    Identificadores
    URI: http://hdl.handle.net/10902/11094
    DOI: 10.1109/ACSSC.2016.7869553
    ISBN: 978-1-5386-3954-2
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    Autoría
    Wang, Yuan; Scharf, Louis L.Autoridad Unican; Santamaría Caballero, Luis IgnacioAutoridad Unican; Wang, Haonan
    Fecha
    2016
    Derechos
    © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
    Publicado en
    50th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 2016, 1159-1163
    Editorial
    IEEE
    Enlace a la publicación
    https://doi.org/ 10.1109/ACSSC.2016.7869553
    Palabras clave
    Passive detection
    MIMO channels
    Passive radar
    Generalized likelihood ratio
    Canonical coordinates
    Resumen/Abstract
    In this work, we consider a two-channel multiple-input multiple-output (MIMO) passive detection problem, in which there is a surveillance array and a reference array. The reference array is known to carry a linear combination of broadband noise and a subspace signal of known dimension but unknown basis. The question is whether the surveillance channel carries a linear combination of broadband noise and a subspace signal of unknown basis, which is correlated with the subspace signal in the reference channel. We consider a second-order detection problem where these subspace signals are structured by an unknown, but common, p-dimensional random vector of symbols transmitted from sources of opportunity, and then received through unknown M × p matrices at each of the M-element arrays. The noises in each channel have arbitrary spatial correlation. We derive the generalized likelihood ratio test (GLRT) statistic and show it is a monotone function of canonical correlations between the reference and surveillance channels.
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    UNIVERSIDAD DE CANTABRIA

    Repositorio realizado por la Biblioteca Universitaria utilizando DSpace software
    Contacto | Sugerencias
    Metadatos sujetos a:licencia de Creative Commons Reconocimiento 4.0 España