Flight Altitude Estimation for Unmanned Aerial Vehicles Using GNSS-Barometer Data Fusion

The emerging frontier in urban transportation, encompassing both goods delivery and passenger transport, is represented by Urban Air Mobility (UAM). UAM seeks to exploit the “third dimension” of airspace to mitigate traffic congestion in daily urban commutes while advancing the decarbonization of transportation systems. UAM is conceived as an innovative transportation mode that utilizes Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, and Vertical Take-Off and Landing (VTOL) vehicles for the aerial transport of people and goods in urban and suburban areas. This class of UAVs will operate in a designated airspace known as Very Low Level (VLL), defined as altitudes below 500 feet. Consequently, accurate altitude measurement will be critical during missions, especially in urban environments where a high level of safety is required. This is due to the presence of people, vehicles, and various obstacles, both stationary and moving, that necessitate precise navigation and obstacle avoidance to ensure safe operations. In this work, a data fusion algorithm that integrates GNSS and barometric measurements is proposed to enhance altitude estimation accuracy, during UAS missions, especially those operations conducted in Beyond Visual Line of Sight (BVLOS) or fully autonomous mode.