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Electrodynamics of the High Latitude Ionosphere. Electrical power (~10^12 W on average), incident over the high latitude ionospheres drives auroral displays, causes magnetic disturbances and other space weather effects over the globe, including Australia. This project uses Iridium, a US$6 billion, commercial satellite constellation, to study energy deposition into the ionosphere from near-Earth space. The Iridium data is not public domain. This project provides data access, representing a signif ....Electrodynamics of the High Latitude Ionosphere. Electrical power (~10^12 W on average), incident over the high latitude ionospheres drives auroral displays, causes magnetic disturbances and other space weather effects over the globe, including Australia. This project uses Iridium, a US$6 billion, commercial satellite constellation, to study energy deposition into the ionosphere from near-Earth space. The Iridium data is not public domain. This project provides data access, representing a significant cost-effective way for Australia to participate in observational space science. Australian postgraduate training is an integral part of the project, providing international level access and interpretation of scientific satellite and over the horizon radar network data.Read moreRead less
Analysis of Polynomial Phase Signals with Missing Observations. Many non-stationary signals in radar, physics and communications can be modelled as polynomial phase signals. These signals are often incomplete due to missing observations from intermittent sensor failures, outliers, receiver errors, periodic interference and inaccessibility of data. The aim of this project is to develop robust and computationally efficient methods for recovering such signals from small data sets when there is a la ....Analysis of Polynomial Phase Signals with Missing Observations. Many non-stationary signals in radar, physics and communications can be modelled as polynomial phase signals. These signals are often incomplete due to missing observations from intermittent sensor failures, outliers, receiver errors, periodic interference and inaccessibility of data. The aim of this project is to develop robust and computationally efficient methods for recovering such signals from small data sets when there is a large proportion of missing observations. This will contribute to a conceptual advancement in the field of signal processing and will provide new methods for use in applications such as radar, astrophysics, seismology, vibration analysis and communications.Read moreRead less