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Field of Research : Dynamical Systems
Socio-Economic Objective : Air transport
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  • Funded Activity

    Linkage Projects - Grant ID: LP0777039

    Funder
    Australian Research Council
    Funding Amount
    $420,000.00
    Summary
    The Acoustic, Control and Aerodynamic Aspects of the Entecho Hoverpod. The development of small aerial vehicles, both manned and unmanned is a growing market in the aviation industry. This market sector has the potential to provide cheap, environmentally friendly transport solutions for the defence purposes, law enforcement agencies and emergency and recreational vehicles. This project serves to enhance Australia's position in this market by helping a local company develop its technology in a .... The Acoustic, Control and Aerodynamic Aspects of the Entecho Hoverpod. The development of small aerial vehicles, both manned and unmanned is a growing market in the aviation industry. This market sector has the potential to provide cheap, environmentally friendly transport solutions for the defence purposes, law enforcement agencies and emergency and recreational vehicles. This project serves to enhance Australia's position in this market by helping a local company develop its technology in a cost effective and timely manner. The progress made in the three research aspects will also advance areas of science and technology with practical applications other than aerial vehicles.
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    Funded Activity

    Discovery Projects - Grant ID: DP0345215

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    Stochastic Geometry for Multi-sensor Data Fusion System. The aim of this project is to develop efficient algorithms for tracking and sensor management in a multi-sensor multi-target environment. Finite random set theory provides a natural way of representing a random number of (random) object states, an issue that has been largely ignored in the tracking literature until recently. Although a satisfactory foundation for multiple object filtering has been provided by random set theory, in this ear .... Stochastic Geometry for Multi-sensor Data Fusion System. The aim of this project is to develop efficient algorithms for tracking and sensor management in a multi-sensor multi-target environment. Finite random set theory provides a natural way of representing a random number of (random) object states, an issue that has been largely ignored in the tracking literature until recently. Although a satisfactory foundation for multiple object filtering has been provided by random set theory, in this early stage no algorithm capable of tracking many targets has emerged from this framework. We are confident that efficient algorithms can be developed by exploiting the insights and mathematical tools of stochastic geometry
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