Efficient Algorithms for Multiple Object Filtering using Stochastic Geometry. The outcomes of this project will enhance our ability to harness advances in sensing and computing technologies and develop automated systems which facilitate rapid and reliable detection and monitoring of potential threats in our air, sea, and land space. Such systems assist our defence personnel in the event of a threat to implement measured and effective responses, and ultimately enhance Australia's operational adva ....Efficient Algorithms for Multiple Object Filtering using Stochastic Geometry. The outcomes of this project will enhance our ability to harness advances in sensing and computing technologies and develop automated systems which facilitate rapid and reliable detection and monitoring of potential threats in our air, sea, and land space. Such systems assist our defence personnel in the event of a threat to implement measured and effective responses, and ultimately enhance Australia's operational advantage, in line with the national research priority of 'Safeguarding Australia' and its associated priority goals. The developed technologies also have significant commercial potential which benefit Australian industries in areas such as robotics, automotive safety and biomedical engineering.Read moreRead less
Performance evaluation and characterisation for filtering in multi-object system. The project falls within the National Research Priority of 'Safeguarding Australia' and associated research priority goal of 'Transforming Defence Technology'. The project outcomes will provide cutting edge technology in surveillance, and monitoring of potential threat in our air, sea, and land space. Fast, reliable information enable our personnel to make timely, intelligent judgements, and appropriate responses i ....Performance evaluation and characterisation for filtering in multi-object system. The project falls within the National Research Priority of 'Safeguarding Australia' and associated research priority goal of 'Transforming Defence Technology'. The project outcomes will provide cutting edge technology in surveillance, and monitoring of potential threat in our air, sea, and land space. Fast, reliable information enable our personnel to make timely, intelligent judgements, and appropriate responses in the event of a threat, thereby maintaining Australia's operational advantage. Other application areas that benefits from our research include radar, sonar, guidance, navigation, air traffic control, image processing, oceanography, autonomous vehicles and robotics, remote sensing, and biomedical research.
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Optimal Control of Multi-Object System. Better understanding of multi-object systems developed from this research, in particular, optimal control algorithms for multi-object systems have several significant socio-economic benefits. Application areas that benefits from our research include aerospace applications such as radar, sonar, guidance, navigation, and air traffic control and non-aerospace areas such as image processing, oceanography autonomous vehicles and robotics, remote sensing, and bi ....Optimal Control of Multi-Object System. Better understanding of multi-object systems developed from this research, in particular, optimal control algorithms for multi-object systems have several significant socio-economic benefits. Application areas that benefits from our research include aerospace applications such as radar, sonar, guidance, navigation, and air traffic control and non-aerospace areas such as image processing, oceanography autonomous vehicles and robotics, remote sensing, and biomedical research. The sensor network discipline also stand to benefit from the understanding of multi-object system and control framework. 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