Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS

Area of Science:

• Aerospace Engineering
• Atmospheric Science
• Robotics

Background:

• Accurate wind profile estimation is crucial for aviation and meteorological applications.
• Traditional methods like SoDAR and anemometers have limitations in spatial coverage and deployment.
• Unmanned Aircraft Systems (UAS) offer a potential platform for localized atmospheric measurements.

Purpose of the Study:

• To develop and validate a model-based approach for estimating vertical wind profiles using a multirotor UAS.
• To assess the feasibility of using a quadrotor's motion perturbations for wind velocity component estimation.
• To investigate the impact of UAS proximity on independent wind measurement instruments.

Main Methods:

• A state estimation framework was adapted to closed-loop rigid body models of a quadrotor.
• System identification algorithms were used to determine quadrotor model structures and parameters for hovering and ascending flight (0-2 m/s).
• The UAS-based wind estimation was experimentally validated against sonic anemometer and SoDAR measurements.

Main Results:

• The quadrotor's wind estimation demonstrated close agreement with independent sensor measurements.
• Horizontal wind velocity profiles were challenging to validate using time-synchronized SoDAR data.
• Close-proximity quadrotor operations were found to potentially corrupt SoDAR wind measurements, a novel finding.

Conclusions:

• The proposed model-based UAS approach provides a viable method for estimating wind velocity profiles.
• The study highlights a previously unreported interference effect of UAS on SoDAR wind measurements.
• Further research is needed to refine UAS-based wind profiling and mitigate interference with other sensors.