Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New ....Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New design methods that deal with noise in an optimal way;
(iii) Noise resistant methods for distributed consensus seeking systems and cooperative control systems.
The outcomes will advance and benefit spatio-temporal data analysis and coordination in areas such as transport, health and video-security.Read moreRead less
Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliabl ....Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliable operation in large complex human systems (such as financial systems) or natural systems (such as gene regulatory networks).Read moreRead less
Radio Frequency Camera for Low-Complexity and High-Resolution Radar Imaging. This project aims to develop the theory and enabling techniques to realise a low-complexity and high-resolution radar imaging system with uncoordinated illumination. New scientific breakthroughs include fundamental radar imaging theory, advanced radio frequency frontend design and fast signal processing algorithms. These will lead to a paradigm shift in active and passive imaging technologies. A proof-of-concept prototy ....Radio Frequency Camera for Low-Complexity and High-Resolution Radar Imaging. This project aims to develop the theory and enabling techniques to realise a low-complexity and high-resolution radar imaging system with uncoordinated illumination. New scientific breakthroughs include fundamental radar imaging theory, advanced radio frequency frontend design and fast signal processing algorithms. These will lead to a paradigm shift in active and passive imaging technologies. A proof-of-concept prototype of the proposed imaging system with 77 GHz millimetre wave will be developed to demonstrate its feasibility and performance. The expected outcomes include Australia’s scientific and technological leadership in radar imaging and enhanced capability in emergency response, defence, public safety, and healthcare industries.Read moreRead less