Profiling the turbulence from spectral measurements in the urban atmosphere using UAVs

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

doi:10.1117/12.2597992

Cited by 2 publications

(10 citation statements)

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“…The theoretical model of ideal quadcopter hovering was proposed in [3,[30][31][32]. One of the main principles of this model is that the components of the quadcopter velocity during hovering are equal to zero relative to the ground.…”

Section: Quadcopter Velocitymentioning

confidence: 99%

“…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%

“…The feasibility of measuring the longitudinal and lateral turbulence spectra was demonstrated in [30], despite the atmospheric hover of a quadcopter not being ideal. The possibility of measuring the turbulence profile is discussed in [31], which presents the longitudinal and lateral turbulence spectra at different heights, as well as the profile of the longitudinal and lateral turbulence scales calculated by the least square fit method for the von Karman model.…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents the results of comparative analysis of the turbulence spectra measured with UAV and an acoustic anemometer and studies the behavior of the turbulence spectra in the inertial and energy-containing ranges. In [3], we partly generalized the experimental results reported in [30][31][32], but the main result was the use of UAV for remote monitoring in an urban environment with complex orography, and turbulence spectra and scales were measured in different seasons (winter, spring, summer, and fall). It was shown in [3,[30][31][32] that to determine the longitudinal and lateral turbulence scales, it is sufficient to measure the profile of the turbulence spectra.…”

Section: Introductionmentioning

confidence: 99%

“…In [3], we partly generalized the experimental results reported in [30][31][32], but the main result was the use of UAV for remote monitoring in an urban environment with complex orography, and turbulence spectra and scales were measured in different seasons (winter, spring, summer, and fall). It was shown in [3,[30][31][32] that to determine the longitudinal and lateral turbulence scales, it is sufficient to measure the profile of the turbulence spectra. Consequently, UAV calibration is not necessary to obtain the result.…”

Section: Introductionmentioning

confidence: 99%

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High-Resolution Profiling of Atmospheric Turbulence Using UAV Autopilot Data

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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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Section: Quadcopter Velocitymentioning

confidence: 99%