Using Small Unmanned Aerial Vehicles for Turbulence Measurements in the Atmosphere

Shelekhov, Alexander P.; Afanasiev, Alexey L.; Shelekhova, E. A.; Kobzev, A. A.; Tel'minov, A E; Molchunov, Alexander; Poplevina, Olga

doi:10.1134/s0001433821050133

Cited by 9 publications

(21 citation statements)

References 20 publications

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“…It was shown in [48] that the results of investigation of the turbulence spectra in the inertial and energy production ranges with the quadcopter in the altitude holding mode over a homogeneous territory are in a good agreement with the theory of homogeneous and isotropic turbulence and with the measurement data obtained using acoustic anemometry. This study allows us to conclude that, in these ranges, at the territory with complex orography, the behavior of the turbulence spectrum measured by the quadcopter agrees with objective data on the state of atmospheric turbulence.…”

Section: Discussionsupporting

confidence: 67%

“…At such a territory and under such weather conditions, obtained experimental data agree well with theoretical results. The capabilities of a hovering quadcopter as applied to the study of homogeneous and isotropic turbulence were examined in [48]. It was shown that the obtained results are in a good agreement with the theory of homogeneous and isotropic turbulence and the data measured by acoustic anemometry methods.…”

Section: Methodsmentioning

confidence: 70%

“…In contrast to a fixed-wing UAV, a quadcopter can hover at a needed point in space for a long time and obtain atmospheric data with the high spatial resolution in an area characterized by complex orography. The results of studying the turbulence spectrum in the inertial and energy production ranges with the DJI Mavic Mini quadcopter in the altitude hold mode are reported in [48]. The measurements were carried out over territory characterized by a flat and uniform surface with a slight slope; it bordered a cottage village on one side and a forest on the other side.…”

Section: Introductionmentioning

confidence: 99%

“…As already mentioned, a quadcopter-in contrast to fixed-wing UAV [36][37][38][39][40][41][42][43][44][45][46][47] and to lidars, sodars, and radars-allows us to obtain atmospheric data with high spatial resolution. Quadcopter capabilities under ideal conditions were examined in [48], in particular, to compare theory with experiment. In this paper, we study the capabilities of a quadcopter for monitoring the state of atmospheric turbulence in an urban area over a territory with complex orography.…”

Section: Introductionmentioning

confidence: 99%

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Low-Altitude Sensing of Urban Atmospheric Turbulence with UAV

Shelekhov

Afanasiev

Shelekhova

et al. 2022

Drones

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The capabilities of a quadcopter in the hover mode for low-altitude sensing of atmospheric turbulence with high spatial resolution in urban areas characterized by complex orography are investigated. The studies were carried out in different seasons (winter, spring, summer, and fall), and the quadcopter hovered in the immediate vicinity of ultrasonic weather stations. The DJI Phantom 4 Pro quadcopter and AMK-03 ultrasonic weather stations installed in different places of the studied territory were used in the experiment. The smoothing procedure was used to study the behavior of the longitudinal and lateral spectra of turbulence in the inertial and energy production ranges. The longitudinal and lateral turbulence scales were estimated by the least-square fit method with the von Karman model as a regression curve. It is shown that the turbulence spectra obtained with DJI Phantom 4 Pro and AMK-03 generally coincide, with minor differences observed in the high-frequency region of the spectrum. In the inertial range, the behavior of the turbulence spectra shows that they obey the Kolmogorov–Obukhov “5/3” law. In the energy production range, the longitudinal and lateral turbulence scales and their ratio measured by DJI Phantom 4 Pro and AMK-03 agree to a good accuracy. Discrepancies in the data obtained with the quadcopter and the ultrasonic weather stations at the territory with complex orography are explained by the partial correlation of the wind velocity series at different measurement points and the influence of the inhomogeneous surface.

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Section: Discussionsupporting

confidence: 67%

Section: Methodsmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Low-Altitude Sensing of Urban Atmospheric Turbulence with UAV

Shelekhov

Afanasiev

Shelekhova

et al. 2022

Drones

View full text Add to dashboard Cite

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“…The results of studying the profiles of the longitudinal and lateral relative spectra of turbulence and the longitudinal and lateral scales of turbulence with a copter-type UAV in a hover mode are presented in [3,[30][31][32]. The theoretical part is considered most thoroughly in [3], where the model of ideal quadcopter hovering in a turbulent atmosphere is proposed.…”

Section: Introductionmentioning

confidence: 99%

High-Resolution Profiling of Atmospheric Turbulence Using UAV Autopilot Data

Shelekhov

Afanasiev

Shelekhova

et al. 2023

Drones

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The capabilities of hovering unmanned aerial vehicles (UAVs) in low-altitude sensing of atmospheric turbulence with high spatial resolution are studied experimentally. The vertical profile of atmospheric turbulence was measured at the Basic Experimental Observatory (Tomsk, Russian Federation) with three quadcopters hovering at altitudes of 4, 10, and 27 m in close proximity (~5 m) to anemometers installed on weather towers. The behavior of the longitudinal and lateral wind velocity components in the 0–10 Hz frequency band is analyzed. In addition, the obtained wind velocity components were smoothed over 1 min by the moving average method to describe long turbulent wind gusts. The discrepancy between the UAV and anemometer data is examined. It is found that after smoothing, the discrepancy does not exceed 0.5 m/s in 95% of cases. This accuracy is generally sufficient for measurements of the horizontal wind in the atmosphere. The spectral and correlation analysis of the UAV and anemometer measurements is carried out. The profiles of the longitudinal and lateral scales of turbulence determined from turbulence spectra and autocorrelation functions are studied based on the UAV and anemometer data.

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