Estimating Turbulence Distribution over a Heterogeneous Path Using Time-Lapse Imagery from Dual Cameras

Wilson, Benjamin; Bose‐Pillai, Santasri R.; McCrae, Jack E.; Keefer, Kevin; Fiorino, Steven T.

doi:10.3390/app11136221

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…In 2019, using a pair of cameras and an LED array, we successfully validated our time-lapse imaging technique with point measurements from four 3D sonic anemometers distributed along a 511 m almost horizontal path. 11 However, using multiple cameras instead of just a pair, can help improve the profiling resolution and the fraction of the path that can be profiled. The multi-camera approach was first tested in summer of 2021 over a 1.9 km slant path using 10 LED sources as imaging targets and then in summer of 2022 with a noncooperative target.…”

Section: Introductionmentioning

confidence: 99%

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Wilson,

Bose,

Freeman

et al. 2023

Unconventional Imaging, Sensing, and Adaptive Optics 2023

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In an earlier work, we demonstrated a method to profile turbulence using time-lapse imagery of a distant target from five spatially separated cameras. Extended features on the target were tracked and by measuring the variances of the difference in wavefront tilts sensed between cameras due to all pairs of target features, turbulence information along the imaging path could be extracted. The method is relatively low cost and does not require sophisticated instrumentation. Turbulence can be sensed remotely from a single site without deployment of sources or sensors at the target location. Additionally, the method is phase-based, and hence has an advantage over irradiance-based techniques which suffer from saturation issues. The same concept has been applied to understand how turbulence changes with altitude in the surface layer. Short exposure images of a 30 m tall water tower were analyzed to obtain turbulence profiles along the imaging path. The experiment was performed over two clear days from mid-morning to early afternoon. The turbulence profiles show a drop in turbulence with altitude as expected. However, the rate at which turbulence decreased with altitude was different close to the ground from at higher altitudes.

show abstract

Section: Introductionmentioning

confidence: 99%

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Wilson,

Bose,

Freeman

et al. 2023

Unconventional Imaging, Sensing, and Adaptive Optics 2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…In 2019, using a pair of cameras and an LED array we successfully validated our time-lapse imaging technique with point measurements from four 3D sonic anemometers distributed along a 511 m almost horizontal path. 6 However, using multiple cameras instead of just a pair, can help improve the profiling resolution and the fraction of the path that can be profiled. The multi-camera approach was first tested in summer of 2021 over a 1.9 km slant path using 10 LED sources as imaging targets.…”

Section: Introductionmentioning

confidence: 99%

Profiling atmospheric turbulence using a non-cooperative target and a camera bank and validating with sonic anemometers

Wilson

Imeri

Bose‐Pillai³

et al. 2022

Unconventional Imaging and Adaptive Optics 2022

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Knowledge of turbulence distribution along a path can be useful for effective compensation in a highly anisoplanatic situation. In an earlier work, a method to profile turbulence using time-lapse imagery of a distant building from two spatially separated cameras was demonstrated. By using multiple cameras instead of just a pair, the profiling resolution as well as the fraction of the path that can be reasonably profiled can be improved. This idea is demonstrated by using 5 spatially separated cameras capturing images of a distant target with features on it. Extended features on the target are tracked and by measuring the variances of the difference in wavefront tilts sensed between cameras due to all pairs of target features, turbulence information along the imaging path can be extracted. The mathematical framework is discussed and the profiling results are compared against point measurements from a 3D sonic anemometer placed onboard an unmanned aerial system which is driven along the imaging path. The method is relatively low cost and does not require sophisticated instrumentation. Turbulence can be sensed remotely from a single site without deployment of sources or sensors at the target location. Additionally, the method is phase-based, and hence has an advantage over irradiance-based techniques which suffer from saturation issues at long ranges. By imaging elevated targets in the future, turbulence changes with altitude can be investigated as well.

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Profiling atmospheric turbulence along a slant path using LEDs and a camera bank

Bose‐Pillai¹,

Wilson

Krone

et al. 2021

Unconventional Imaging and Adaptive Optics 2021

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Estimating Turbulence Distribution over a Heterogeneous Path Using Time-Lapse Imagery from Dual Cameras

Cited by 5 publications

References 11 publications

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Profiling atmospheric turbulence using a non-cooperative target and a camera bank and validating with sonic anemometers

Profiling atmospheric turbulence along a slant path using LEDs and a camera bank

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