DOB-based Wind Estimation of A UAV Using Its Onboard Sensor

TL;DR

This paper introduces a comprehensive 3-D wind estimation algorithm for UAVs that improves accuracy, range, and adaptability, validated through wind tunnel experiments.

Contribution

The proposed algorithm enables accurate 3-D wind estimation during dynamic UAV flight and is adaptable across different UAV platforms.

Findings

Wind speed accuracy of 0.11 m/s

Wind direction error less than 2.8 degrees

Measurement range extended to 10 m/s

Abstract

Unmanned Aerial Vehicles (UAVs) play a crucial role in meteorological research, particularly in environmental wind field measurements. However, several challenges exist in current wind measurement methods using UAVs that need to be addressed. Firstly, the accuracy of measurement is low, and the measurement range is limited. Secondly, the algorithms employed lack robustness and adaptability across different UAV platforms. Thirdly, there are limited approaches available for wind estimation during dynamic flight. Finally, while horizontal plane measurements are feasible, vertical direction estimation is often missing. To tackle these challenges, we present and implement a comprehensive wind estimation algorithm. Our algorithm offers several key features, including the capability to estimate the 3-D wind vector, enabling wind estimation even during dynamic flight of the UAV. Furthermore, our algorithm exhibits adaptability across various UAV platforms. Experimental results in the wind tunnel validate the effectiveness of our algorithm, showcasing improvements such as wind speed accuracy of $0.11$ m/s and wind direction errors of less than $2.8^\circ$. Additionally, our approach extends the measurement range to $10$ m/s.