Characterizing turbulence profile layers through celestial single-source observations

Abstract

Future spacecraft missions aim to communicate with the Earth using near-infrared lasers. The possible bit rate of Free-Space Optical Communication (FSOC) is orders of magnitude greater when compared to current Radio Frequency (RF) transmissions. The challenge of groundspace FSOC is that atmospheric turbulence perturbs optical wavefront propagation. These wavefront aberrations can be measured using a Shack-Hartmann Wavefront Sensor (SHWFS). A ground-based Adaptive Optics (AO) system can mitigate these aberrations along the optical path by translating wavefront measurements into Deformable Mirror (DM) commands. However, errors result from atmospheric turbulence continuously evolving and there being unavoidable delays during AO wavefront correction. The length of an acceptable delay is referred to as the coherence time -a parameter dependent on the strength of turbulence profile layers and their corresponding wind-driven velocity. This study introduces a novel technique for using SHWFS single-source observations, e.g. the downlink signal from a geostationary satellite, to measure the strength and velocity of turbulence profile layers. This work builds upon previous research and demonstrates that single-source observations can disentangle turbulence profile layers through studying the cross-covariance of temporally offset SHWFS centroid measurements. Simulated data is used to verify that the technique can recover the coherence time. The expected and measured results have a correlation coefficient of 0.95.

Pre-distortion adaptive optics: experimental results from bi-directional tracking links between DLR’s optical ground station and Alphasat’s TDP-1 terminal

“…This reduction in scintillation is clearly observed as a reduction in power fades during the time that the pre-distortion AO system is on. A larger Fried parameter value of r0 = 9.2 cm (specified at 500 nm and at Zenith) was extracted from the WFS measurements for this link through a single-source observation technique, 21 thus quantifying the weaker turbulence conditions that were present.…”

Reconstruction error analysis in LGS tomography for adaptive optics applications

“…In pursuit of a comprehensive analysis, we have developed a MATLAB-based algorithm implementing the Learn & Apply (L&A) technique for tomographic reconstructions in LTAO systems. [1][2][6][7][8][9][10][11] Our primary objective is to assess the level of reconstruction errors encountered during the L&A algorithm's application.…”

Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model

“…The refractive index structure constant, C 2 n , has been used as an indicator to characterize and quantify the turbulent spatial fluctuations caused by temperature gradients [1,2], wherein n denotes the local refractive index of the atmosphere. Existing techniques for C 2 n measurements include scintillation detection and ranging (SCIDAR) [3], multiaperture scintillation sensor (MASS) [4,5], scintillator [6], Shack Hartmann wavefront sensor (SHWFS) [7][8][9][10][11][12][13], Differential Image Motion (DIM) Light Detection and Ranging (LIDAR) [14], acoustic meteorological radar (sodar) [15], and the balloon-borne microthermometry [16]. Indeed, various techniques exist for the measurement of C 2 n (h).…”