Acoustic localisation for real-life applications of wireless sensor networks

  • Michael Allen

    Student thesis: Doctoral ThesisDoctor of Philosophy


    The work described in this thesis is concerned with self-localisation (automated estimation of sensor locations) and source-localisation (location of a target) using Wireless Sensor Networks (WSNs). The motivation for the research in this thesis is the on-line localisation of marmots from their alarm calls. The application requires accurate 3D self-localisation (within a small percentage of sensor spacing) as well as timely operation. Further challenges are added by the high data-rate involved: sensor nodes acquire data at a rate that is greater than the available network bandwidth. This data cannot be streamed over a multi-hop network, implying a need for data reduction through in-network event detection and local data compression or filtering techniques. The research approach adopted in this thesis combined simulation, emulation and real-life experimentation. Real-life deployment and experimentation highlighted problems that could not be predicted in controlled experiments or simulation. Emulation used data gathered from controlled, real-life experimentation to simulate proposed system refinements; this was sufficient to provide a proof-of-concept validation for some of the concepts developed. Simulation allowed the understanding of underlying theoretical behaviour without involving the complex environmental effects caused by real-life experimentation. This thesis details contributions in two distinct aspects of localisation: acoustic ranging and end-toend deployable acoustic source localisation systems. With regard to acoustic ranging and 3D localisation, two WSN platforms were evaluated: one commercially available, but heavily constrained (Mica2) and one custom-built for accurate localisation (Embedded Networked Sensing Box (ENSBox)). A new proof of concept platform for acoustic sensing (based on the Gumstix single-board computer) was developed by the author (including the implementation of a ranging mechanism), based on experiences with the platforms above. Furthermore, the literature was found to lack a specific procedure for evaluation and comparison of self-localisation algorithms from theoretical conception to real-life testing. Therefore, an evaluation cycle for self-localisation algorithms that encompassed simulation, emulation and real-life deployment was developed. With respect to source localisation, a hardware and software platform named VoxNet was designed and implemented.

    Date of Award2009
    Original languageEnglish
    Awarding Institution
    • Coventry University
    SupervisorElena Gaura (Supervisor)


    • Wireless sensor networks
    • WSNs

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