Geintra

Departamento de electronica Universidad de Alcala

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    Acoustic Sensor Network for Relative Positioning of Nodes

    TítuloAcoustic Sensor Network for Relative Positioning of Nodes
    Tipo de publicaciónJournal Article
    Año de publicación2009
    AutoresMarzziani, CD, Ureña, J, Hernández, Á, Mazo, M, Garcia, JJ, Jimenez, A, del Perez, MC, Álvarez, FJ, Villadangos, JM
    Idioma de publicaciónEnglish
    Revista académicaSensors
    Volumen9
    Número11
    Páginas8490 - 8507
    Fecha de publicación11/2009
    Rank in category11/56
    JCR CategoryInstrumentation and Measurements
    Palabras clavesensor networks; relative localization; remote sensing
    JCR Impact Factor1.870
    ISSN1424-8220
    DOI10.3390/s91108490
    Resumen

    In this work, an acoustic sensor network for a relative localization system is analyzed by reporting the accuracy achieved in the position estimation. The proposed system has been designed for those applications where objects are not restricted to a particular environment and thus one cannot depend on any external infrastructure to compute their positions. The objects are capable of computing spatial relations among themselves using only acoustic emissions as a ranging mechanism. The object positions are computed by a multidimensional scaling (MDS) technique and, afterwards, a least-square algorithm, based on the Levenberg-Marquardt algorithm (LMA), is applied to refine results. Regarding the position estimation, all the parameters involved in the computation of the temporary relations with the proposed ranging mechanism have been considered. The obtained results show that a fine-grained localization can be achieved considering a Gaussian distribution error in the proposed ranging mechanism. Furthermore, since acoustic sensors require a line-of-sight to properly work, the system has been tested by modeling the lost of this line-of-sight as a non-Gaussian error. A suitable position estimation has been achieved even if it is considered a bias of up to 25 of the line-of-sight measurements among a set of nodes.