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Research Topic : AIR POLLUTION
Australian State/Territory : NSW
Field of Research : Signal Processing
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  • Funded Activity

    Linkage Projects - Grant ID: LP0349117

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    Development of an active noise control system for sleeper seats on large commercial aircraft. Possible avenues will be investigated to actively reduce aircraft cabin noise experienced by passengers in sleeper seats, using localised active noise control (ANC). Previous work has focused on headsets and upright seat headrests which represent a different problem to the partially enclosed sleeper seats considered here. Efficiency and robustness problems that affect existing ANC systems will be addres .... Development of an active noise control system for sleeper seats on large commercial aircraft. Possible avenues will be investigated to actively reduce aircraft cabin noise experienced by passengers in sleeper seats, using localised active noise control (ANC). Previous work has focused on headsets and upright seat headrests which represent a different problem to the partially enclosed sleeper seats considered here. Efficiency and robustness problems that affect existing ANC systems will be addressed. A prototype system will be produced for a business class sleeper seat in a wide body aircraft. A second outcome is the establishment of a robust integrated system design procedure that can be used to quickly develop ANC systems for future designs.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100252

    Funder
    Australian Research Council
    Funding Amount
    $361,087.00
    Summary
    Protecting Critical Transport Infrastructure using Hybrid Approaches for Interference and Spoofer Detection and Localisation. Modern infrastructure increasingly relies on the positioning and timing capabilities provided by the Global Navigation Satellite Systems (GNSS). GNSS signals, however, are vulnerable to interference and spoofing attacks. This vulnerability is aggravated as satellite navigation becomes more central to the operation of airports, ports, railways, and communications systems. .... Protecting Critical Transport Infrastructure using Hybrid Approaches for Interference and Spoofer Detection and Localisation. Modern infrastructure increasingly relies on the positioning and timing capabilities provided by the Global Navigation Satellite Systems (GNSS). GNSS signals, however, are vulnerable to interference and spoofing attacks. This vulnerability is aggravated as satellite navigation becomes more central to the operation of airports, ports, railways, and communications systems. Building on from earlier work by University of New South Wales, University of Adelaide and GPSat Systems, this project aims to create a system for locating interference and spoofers to GNSS of any power in real time, providing layered monitoring and reactive mitigation solutions against interference and spoofing attacks.
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    Funded Activity

    Discovery Projects - Grant ID: DP0346258

    Funder
    Australian Research Council
    Funding Amount
    $172,536.00
    Summary
    Bayesian inference for complex regression models using mixtures. The project will use mixtures to flexibly model complex regression functions and will develop Bayesian methods for carrying out statistical inference on these models. The models will deal with both Gaussian and non-Gaussian data. Multiple explanatory variables are dealt with by mixing simple additives to produce flexible high dimensional function estimates. Variable selection and model averaging will be used to identify important v .... Bayesian inference for complex regression models using mixtures. The project will use mixtures to flexibly model complex regression functions and will develop Bayesian methods for carrying out statistical inference on these models. The models will deal with both Gaussian and non-Gaussian data. Multiple explanatory variables are dealt with by mixing simple additives to produce flexible high dimensional function estimates. Variable selection and model averaging will be used to identify important variables and thus make the estimation more efficient. The methods will be extended to multivariate responses where account will taken be taken of the structure of the dependence between responses.
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    Funded Activity

    Discovery Projects - Grant ID: DP0986391

    Funder
    Australian Research Council
    Funding Amount
    $260,000.00
    Summary
    Novel time-frequency techniques for analysing and modeling non-stationary physical and engineering data. This project addresses an issue of fundamental importance in science and technology, where non-stationary data (which have time-varying statistics) are ubiquitous. Therefore, the development of time-frequency tools to model and analyse non-stationary data has great potential for impact in a wide range of areas reaching from seismic data analysis to biomedical signal processing to sonar and ra .... Novel time-frequency techniques for analysing and modeling non-stationary physical and engineering data. This project addresses an issue of fundamental importance in science and technology, where non-stationary data (which have time-varying statistics) are ubiquitous. Therefore, the development of time-frequency tools to model and analyse non-stationary data has great potential for impact in a wide range of areas reaching from seismic data analysis to biomedical signal processing to sonar and radar. Employing techniques to be developed in this proposal, we expect to be able to classify and detect features of non-stationary data that were unrecognisable using hitherto known methods.
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