The objective of this study is to explore the feasibility and accuracy of image subtraction for estimating optical turbulence. The proposed approach involves creating a differential image by subtracting consecutive recorded frames. Post processing techniques are applied to the differential image, allowing temporal changes caused directly by turbulence to be identified. Image subtraction was implemented in python and evaluated against traditional turbulence instruments such as a Scintec BLS2000 and a MZA DELTA.
This research paper discusses the application of several image-based techniques for measuring optical turbulence. University of Central Florida researchers have previously prototyped and fielded a differential disturbance tracker at the TISTEF 1 kilometer range. This effort has evolved into the development of a software suite that implements image processing techniques such as blob detection, centroid tracking, and optical flow for estimating the refractive index structure parameter. To validate each method, imagery was collected over the 1 kilometer path. The processed results were compared against measurements from an MZA DELTA system.
Experiments were conducted at the TISTEF laser range to evaluate the atmospheric turbulence data of several instruments. A Scintec BLS900, BLS2000, SLS20, MZA DELTA, and an Applied Technologies SATI-3A sonic anemometer were deployed on the 1 kilometer range and recorded measurements over a multi-day period. The data was then processed to compare the calculated refractive index structure parameter (C2n ) between the instruments. The BLS2000 and DELTA were also deployed to record turbulence measurements along a 13.5 kilometer slant path from the TISTEF site to the Vehicle Assembly Building roof on Kennedy Space Center property for additional evaluation.
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