Creating a Perceptive Mobile Network Using Joint Communication and Sensing. This project aims to develop foundational technologies for an innovative perceptive mobile (cellular) communication network that is also capable of ubiquitous radio sensing. It is expected to generate groundbreaking theorems and algorithms that will significantly advance the knowledge of joint communication and sensing. The intended outcomes are an innovative large-scale sensing solution capable of real-time 3D-plus radi ....Creating a Perceptive Mobile Network Using Joint Communication and Sensing. This project aims to develop foundational technologies for an innovative perceptive mobile (cellular) communication network that is also capable of ubiquitous radio sensing. It is expected to generate groundbreaking theorems and algorithms that will significantly advance the knowledge of joint communication and sensing. The intended outcomes are an innovative large-scale sensing solution capable of real-time 3D-plus radio imaging of the world, and enhanced communications with improved quality and reliability. The technology will revolutionize traditional communication-only mobile networks. It will enable and boost expansive radio sensing applications in e.g. transportation, energy, agriculture, and security.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101181
Funder
Australian Research Council
Funding Amount
$403,775.00
Summary
Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multipl ....Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multiple mobile agents (e.g. vehicle) to enhance their ability to anticipate situations in dynamic environments and to act effectively to enhance safety. This should provide benefits for the development of cooperative autonomous driving to enhance road safety.Read moreRead less