  The strength and vertical distribution of atmospheric turbulence is a key
factor determining the performance of optical and infrared telescopes, with and
without adaptive optics. Yet, this remains challenging to measure. We describe
a new technique using a sequence of short-exposure images of a star field,
obtained with a small telescope. Differential motion between all pairs of star
images is used to compute the structure functions of longitudinal and
transverse wavefront tilt for a range of angular separations. These are
compared with theoretical predictions of simple turbulence models by means of a
Markov-Chain Monte-Carlo optimization. The method is able to estimate the
turbulence profile in the lower atmosphere, the total and free-atmosphere
seeing, and the outer scale. We present results of Monte-Carlo simulations used
to verify the technique, and show some examples using data from the second AST3
telescope at Dome A in Antarctica.
