Wind Estimation with Multirotor UAVs

Abstract

Unmanned Aerial Vehicles (UAVs) have benefited from a tremendous increase in popularity over the past decade, which has inspired their application toward many novel and unique use cases. One of them is the use of UAVs in meteorological research, in particular for wind measurement. Research in this field using quadcopter UAVs has shown promising results. However, most of the results in the literature suffer from three main drawbacks. First, experiments are performed as numerical simulations or in wind tunnels. Such results are limited in their validity in real-life conditions. Second, it is almost always assumed that the drone is stationary, which limits measurements spatially. Third, no attempts at estimating vertical wind are made. Overcoming these limitations offer an opportunity to gain significant value from using UAVs for meteorological measurements. We address these shortcomings by proposing a new dynamic model-based approach, that relies on the assumption that thrust can be measured or estimated, while drag can be related to air speed. Moreover, the proposed method is tested on empirical data gathered on a DJI Phantom 4 drone. During hovering, our method leads to precision and accuracy comparable to existing methods that use tilt to estimate the wind. At the same time, the method is able to estimate wind while the drone is moving. This paves the way for new uses of UAVs, such as the measurement of shear wind profiles, knowledge of which is relevant in Atmospheric Boundary Layer (ABL) meteorology. Additionally, since a commercial off-the-shelf drone is used, the methodology can be replicated by others without any need for custom hardware development or modifications.

Estimation of Atmospheric Gusts Using Integrated On-Board Systems of a Jet Transport Airplane—Flight Simulations

“…Taking into consideration dependencies (1), ( 2), ( 12), ( 13) and ( 17), the complete law of headwind estimation (including temporary gusts) can be formulated as (18), and finally, as Equation (19).…”

“…The proposed architecture does not require any mathematical modelling of the system and is computationally inexpensive [27]. The cascaded Taking into consideration dependencies (1), ( 2), ( 12), ( 13) and ( 17), the complete law of headwind estimation (including temporary gusts) can be formulated as (18), and finally, as Equation (19).…”

“…In order to reduce delays in the wind parameter estimation process and exclude the influence of airplane control on the obtained result, inertial measurements and flight dynamics are also taken into account [15][16][17]. A gust of the same intensity acting on a small airplane or an unmanned aerial vehicle (UAV) [18][19][20] has a different impact on its accelerations than acting on an airplane which weigh a dozen tons [21]. Massive airplanes' responses are slower and more delayed in time.…”

Evaluation of drag coefficient for a quadrotor model

“…Outdoor flights have been performed in [9,7] and comparison between ground reference measurements are made, showing the feasibility of wind measurement from quadrotors based on IMU and GPS measurements. Note that estimating the vertical components of the wind requires an accurate modeling of the propulsion system and despite that, have not shown satisfactory results in [12].…”

Management and Regulation of Drone Operation in Urban Environment: A Case Study

“…Drones, generally unmanned aerial vehicles/systems-UAV/UAS-were initially only utilized for military applications. However, they have recently been widely used in civil applications in many domains such as disaster management (Mohd Daud et al 2022), the delivery of goods and information (Henderson et al 2019), search operations (Kyriakakis et al 2021); (Martinez-Alpiste et al 2021), surveillance (Dilshad et al 2020), managing wildfires (Bailon-Ruiz and Lacroix 2020), relay for ad hoc networks (Park et al 2018); (He et al 2020), wind estimation (Meier et al 2022), civil security (Hildmann and Kovacs 2019), agricultural and remote sensing (Zhang et al 2021), traffic monitoring (Khan et al 2020), healthcare and health-related services (Kim et al 2017); (Comtet and Johannessen 2021); (Hiebert et al 2020), and emergency medical services (Pulsiri and Vatananan-Thesenvitz 2020). Moreover, one of the most evolving areas of drones is their involvement in smart cities, where society and policymakers are continuously working on their developments (Bohloul 2020).…”