Discovery Early Career Researcher Award - Grant ID: DE120101266
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Low-complexity factor-graph-based receiver design for bandwidth-efficient communication systems over doubly selective channels. This project aims to solve challenging problems in future wireless communications using graph-based signal processing techniques. It will provide practical solutions for future broadband mobile communications to the bush and high-speed underwater acoustic communications in the oceans that are particularly important to Australia.
Blind separation of mutually correlated sources. This project is aimed at developing novel techniques for blind separation of mutually correlated sources. The expected outcomes will significantly advance the theory of blind source separation and improve the performance of important practical systems, such as densely deployed sensor networks and wireless video surveillance systems.
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed ....Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed methodology enables quantification of confidence in the predictions. This will provide ship owners, directly to their vessels and/or at the fleet management centres, information such as weather reports, reliable collision/no-collision warnings and avoidance strategies, on-the-fly. Read moreRead less
A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, th ....A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, this project seeks to develop new distributed solutions for statistical estimation, which are specifically designed for dynamic systems with multiple object states, and are inherently scalable and robust. The potential benefits include new technologies for smart cities, autonomous infrastructure, and digital productivity.Read moreRead less
Signal Processing for Reconfigurable Antennas – a Multidisciplinary Approach for Next Generation Wireless Communications. To satisfy the enormous demand for wireless applications with scarce radio spectrum, new technologies must be researched, developed, and then employed. Reconfigurable antennas, through morphing their physical structures with various switches, can adapt to the radio propagation environment, thereby increasing spectrum efficiency and power efficiency of wireless communications. ....Signal Processing for Reconfigurable Antennas – a Multidisciplinary Approach for Next Generation Wireless Communications. To satisfy the enormous demand for wireless applications with scarce radio spectrum, new technologies must be researched, developed, and then employed. Reconfigurable antennas, through morphing their physical structures with various switches, can adapt to the radio propagation environment, thereby increasing spectrum efficiency and power efficiency of wireless communications. This project aims to design signal processing algorithms for achieving all the benefits that reconfigurable antennas can provide for wireless communications. An important outcome of this research is sound channel models validated by extensive field measurement data.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102388
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
From Bayesian filtering to smoothing and prediction for multiple object systems. This project will develop new and improved algorithms for tracking multiple targets, such as tanks, submarines or planes, using the state of the art in mathematical and computational design. These will enable more efficient and accurate technologies for defence related applications including intelligence, surveillance and reconnaissance.
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
Parameter estimation for multi-object systems. Parameter estimation in multi-object system is essential to the application of multi-object filtering to a wider range of practical problems with social and commercial benefits. This project develops the necessary parameter estimation techniques for complete 'plug-and-play' multi-object filtering solutions that facilitates widespread applications.
Automated On-Line Analysis and Contaminant Detection in Mineral Ore Processing. On-belt analysis is a key to efficient functioning of several
industries involved in the mining and use of minerals. It provides
chemical analysis of the minerals as they run through the instrument
on a conveyer belt. It permits quality control and detection of
impurities. The Scantech on-line analyser is at the forefront of this
technology. Our aim is to produce novel techniques to significantly
improve and m ....Automated On-Line Analysis and Contaminant Detection in Mineral Ore Processing. On-belt analysis is a key to efficient functioning of several
industries involved in the mining and use of minerals. It provides
chemical analysis of the minerals as they run through the instrument
on a conveyer belt. It permits quality control and detection of
impurities. The Scantech on-line analyser is at the forefront of this
technology. Our aim is to produce novel techniques to significantly
improve and make more efficient the processing of data from the
analyser. A particular focus will be quicker and improved calibration
of the instrument. These techniques will increase the accuracy and
speed while reducing the costs of such analysers, thus retaining and
enhancing their competitiveness in the global market.
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