Generating nonstationary multisensor signals under a spatial coherence constraint

Emanuël A.P. Habets, Israel Cohen, Sharon Gannot

    Research output: Contribution to journalArticlepeer-review

    128 Scopus citations

    Abstract

    Noise fields encountered in real-life scenarios can often be approximated as spherical or cylindrical noise fields. The characteristics of the noise field can be described by a spatial coherence function. For simulation purposes, researchers in the signal processing community often require sensor signals that exhibit a specific spatial coherence function. In addition, they often require a specific type of noise such as temporally correlated noise, babble speech that comprises a mixture of mutually independent speech fragments, or factory noise. Existing algorithms are unable to generate sensor signals such as babble speech and factory noise observed in an arbitrary noise field. In this paper an efficient algorithm is developed that generates multisensor signals under a predefined spatial coherence constraint. The benefit of the developed algorithm is twofold. Firstly, there are no restrictions on the spatial coherence function. Secondly, to generate M sensor signals the algorithm requires only M mutually independent noise signals. The performance evaluation shows that the developed algorithm is able to generate a more accurate spatial coherence between the generated sensor signals compared to the so-called image method that is frequently used in the signal processing community.

    Original languageEnglish
    Pages (from-to)2911-2917
    Number of pages7
    JournalJournal of the Acoustical Society of America
    Volume124
    Issue number5
    DOIs
    StatePublished - Nov 2008

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