Intellectual Merits: The objective of this project is to develop information theory and signal processing-based algorithms for Heterogeneous Sensor Networks (HSN) that jointly addresses sensor adaptation and data fusion in the presence of a combination of stationary or non-stationary heterogeneous sensors in constrained environments. Two research thrusts will be investigated: 1) information theory for HSN design; 2) signal processing for HSN information integration. Current research on the theory and algorithms of HSN is very limited. There exist a number of fundamental problems that have never been addressed, yet they are critical to the HSN. To tackle these problems, novel approaches and methodologies that will incorporate techniques such as information theory, network science, collaborative signal processing, estimation theory, statistical approach, and optimization will be studied and therefore has the potential to inspire transformative methodologies that could be applied to many domains. The proposed theories will lead to practical methodologies, algorithms and design tools with performance robust to uncertainty and adaptive to variations in dynamic operating conditions.
Broader Impacts: This project will make a significant contribution to the applications of HSN and will have a broad and deep social impact. Because of the vast amounts of real-time information coming from many widely distributed sources in homeland security and defense, HSN is needed to collect and process threat-related information to insure that it is not overlooked. A carefully developed, research-centric education plan is also proposed. Under-represented and female students will be recruited from different societies for this project.
