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.
3D tomographic reconstruction of rainfall using satellite signals. This project aims to use the microwave communication links of low earth and/or medium earth orbit satellites to achieve three dimensional tomographic reconstruction of rainfall. The path loss of microwave signals due to rainfall, known as rain attenuation can be used to measure rain. Similar to using X-ray to carry out human-body CT scans. With the aid of advanced signal processing techniques, the proposed method will achieve 3D ....3D tomographic reconstruction of rainfall using satellite signals. This project aims to use the microwave communication links of low earth and/or medium earth orbit satellites to achieve three dimensional tomographic reconstruction of rainfall. The path loss of microwave signals due to rainfall, known as rain attenuation can be used to measure rain. Similar to using X-ray to carry out human-body CT scans. With the aid of advanced signal processing techniques, the proposed method will achieve 3D measurements with resolution and coverage unachievable before, paving the way for innovative water relevant applications such as hydrology and agriculture, and new findings in atmospheric research.Read moreRead less
A stochastic geometric framework for Bayesian sensor array processing. This project develops a mathematical framework, and a new generation of techniques, for sensor array processing to address real-world problems with uncertainty in array parameters and number of signals. The outcomes will enhance the capability of sensors in many application areas including, radar, sonar, astronomy and wireless communications.