Share Email Print
cover

Proceedings Paper

Profiling atmospheric turbulence using time-lapse imagery from two cameras
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

For effective turbulence compensation, especially in highly anisoplanatic scenarios, it is useful to know the turbulence distribution along a path. Irradiance-based techniques suffer from saturation when profiling turbulence over long ranges and hence alternate techniques are currently being explored. In an earlier work, a method to estimate turbulence parameters such as path weighted Cn2 and Fried’s coherence length r0 from turbulence induced random, differential motion of extended features in the time-lapse imagery of a distant target was demonstrated. A technique to measure the distribution of turbulence along an experimental path using the time-lapse imagery of a target from multiple cameras is presented in this work. The approach uses an LED array as target and two cameras separated by a few feet at the other end of the path imaging the LED board. By measuring the variances of the difference in wavefront tilts sensed by a single camera and between the two cameras due to a pair of LEDs with varying separations, turbulence information along the path can be extracted. The mathematical framework is discussed and the technique has been applied on experimental data collected over a 600 m approximately horizontal path over grass. A potentially significant advantage of the method is that it is phase based, and hence can be applied over longer paths. The ultimate goal of this work is to profile turbulence remotely from a single site using targets of opportunity. Imaging elevated targets over slant paths will help in better understanding how turbulence varies with altitude in the surface layer.

Paper Details

Date Published: 14 May 2019
PDF: 12 pages
Proc. SPIE 11001, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX, 1100112 (14 May 2019); doi: 10.1117/12.2519022
Show Author Affiliations
Santasri R. Bose-Pillai, Air Force Institute of Technology (United States)
Applied Research Solutions (United States)
Jack E. McCrae Jr., Air Force Institute of Technology (United States)
Aaron J. Archibald, Air Force Institute of Technology (United States)
Christopher A. Rice, Air Force Institute of Technology (United States)
Steven T. Fiorino, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 11001:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX
Gerald C. Holst; Keith A. Krapels, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray