METSIS: Hyperlocal Wind Nowcasting for U-space

METSIS: Hyperlocal Wind Nowcasting for U-space

Sun, Junzi (TU Delft Control & Simulation)
Sunil, Emmanuel (Royal Netherlands Aerospace Centre NLR)
Koerse, Ralph (Royal Netherlands Aerospace Centre NLR)
van Selling, Stijn (Royal Netherlands Aerospace Centre NLR)
van Doorn, Jan-Willem (Royal Netherlands Aerospace Centre NLR)
Brinkman, Thomas (AirHub)

2021

The METeo Sensors in the Sky (METSIS) project, funded by SESAR’s Engage knowledge transfer network, investigated the use of drones as an aerial wind sensor network for U-space applications. The concept aims to provide accurate, lowcost and hyperlocal wind nowcasts for drones using data collected by drones themselves and the Meteo-Particle Model (MPM) for wind field reconstruction. In this paper, we describe the METSIS concept and a proof-of-concept experiment that was performed using four drones to determine the feasibility and accuracy of the concept at low altitudes. For the experiment, ultrasonic anemometers were mounted to each drone to measure local winds. The calibration of the wind sensors was tested using the NLR Anechoic Wind Tunnel. Subsequently, flight-tests were performed at the NLR Drone Center to evaluate the effect of obstacles, drone motion, measurement density, and measurement errors on concept accuracy. Wind fields estimated during the flight-tests were published to the AirHub Drone Operations Center (DOC) system to demonstrate the communication of this data to U-space end-users in real-time. The results indicated that the METSIS concept is a promising solution for the wind nowcast component of the U-space weather information service. Further research is planned to improve the accuracy and sclability of the METSIS concept.

U-space
Weather Information Service
Meteo Particle Model (MPM)
UTM
Drones

http://resolver.tudelft.nl/uuid:c8739127-332b-4bee-a5fe-1f51baca5137

11th SESAR Innovation Days

11th SESAR Innovation Days, 2021-12-07 → 2021-12-09, virtual event

Institutional Repository

conference paper

© 2021 Junzi Sun, Emmanuel Sunil, Ralph Koerse, Stijn van Selling, Jan-Willem van Doorn, Thomas Brinkman