  Supernova remnants (SNRs) exhibit varying degrees of anisotropy, which have
been extensively modeled using numerical methods. We implement a technique to
measure anisotropies in SNRs by calculating power spectra from their
high-resolution images. To test this technique, we develop 3D hydrodynamical
models of supernova remnants and generate synthetic x-ray images from them.
Power spectra extracted from both the 3D models and the synthetic images
exhibit the same dominant angular scale, which separates large scale features
from small scale features due to hydrodynamic instabilities. The angular power
spectrum at small length scales during relatively early times is too steep to
be consistent with Kolmogorov turbulence, but it transitions to Kolmogorov
turbulence at late times. As an example of how this technique can be applied to
observations, we extract a power spectrum from a \textit{Chandra} observation
of Tycho's SNR and compare with our models. Our predicted power spectrum picks
out the angular scale of Tycho's fleece-like structures and also agrees with
the small-scale power seen in Tycho. We use this to extract an estimate for the
density of the circumstellar gas ($n \sim 0.28/\mathrm{cm^3}$), consistent with
previous measurements of this density by other means. The power spectrum also
provides an estimate of the density profile of the outermost ejecta. Moreover,
we observe additional power at large scales which may provide important clues
about the explosion mechanism itself.
