The angle of incidence for reflectometer channels is shown for imperfect imaging conditions. The cutoff surface is shown at left. Incident wave is normal to the curoff, while observed reflected beams are normal to the cutoff surface at midplane channels and have an angle q with respect to the surface normal at edge channels.
Contours of constant correlations between density fluctuations at the cutoff surface and phase fluctuations at the image plane are shown. In (a), the receiver is focused at the midplane and at normal reflection. In (b), contours for the same range of fluctuations are shown, but the receiver is focused 19.3 cm below the midplane with a 10° viewing angle. The highlighted curves refer to the minimum acceptable correlation.
Measurement with fluctuation wavenumber 0.7 cm−1, and fluctuation level 0.1%. (a) The synthetic diagnostic signal is plotted in the complex plane (IQ plot). (b) The phase of this signal (blue) is compared to the density fluctuation at the cutoff surface (red). (c) The spectrum of the measured signal (blue), matches well with the spectrum of the density fluctuations on the cutoff surface (red). (d) Shows the same spectral comparison for a channel measured at 19.3 cm below the midplane.
Spectra are compared for (a) wavenumber of 7 cm−1, and (b) wavenumber of 9 cm−1. Though these cases are far beyond the spatial Nyquist criterion, the main frequencies still match very well.
The correlations are plotted for broadband turbulence with wavenumbers centered at 0 cm−1. The x axis is the Gaussian distribution variation, and the y axis is the fluctuation level. The maximum variation and fluctuation level for correlation values larger than 0.6 are 2.6 cm−1 and 0.3%.
A spectral comparison between fluctuations at the cutoff surface (red) and the synthetic diagnostic signal (blue) is shown for (a), fluctuations with Gaussian distribution variation of 0.5 cm−1, and (b), Gaussian distribution variation of 4.0 cm−1. The fluctuation level is 0.1%. Each plot consists of 5000 time points. A Gaussian fit to the fluctuation data is shown as the white curve.
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