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Monitoring and Improving Positioning Integrity for Unmanned Aerial Vehicles (UAVs)
Grace Gao
Fellow 2017-18

To safely navigate in the coming age of autonomous systems, positioning is critical. The Global Positioning System (GPS), providing absolute position information, is a significant component of Unmanned Aerial Vehicles (UAVs). GPS operates via satellite signal reception and is thus susceptible to satellite and signal propagation errors. In urban environments, GPS signals can be blocked or reflected by buildings, leading to incorrect positioning, and thus resulting in potentially catastrophic failures of the autonomous platforms. To ensure safe and reliable positioning of autonomous systems, it is critical to address not only positioning accuracy, but also the confidence in accuracy, defined as integrity.

Professor Gao proposes a novel positioning integrity assessment and monitoring solution that is robust in GPS-challenged environments and is suitable for navigation sensor fusion. 1) She will develop a new algorithm to directly assess and monitor GPS integrity in urban environments; 2) she will develop an integrity-monitoring framework for GPS sensor fusion using camera vision, Lidar and inertial measurements; 3) she will further improve integrity by turning unwanted multipath signals into a useful navigational source. The proposed solutions will be assessed by conducting real-world flight tests using the UAV fleets in Professor Gao’s lab.