  For line spectrum estimation, we derive the maximum a posteriori probability
estimator where prior knowledge of frequencies is modeled probabilistically.
Since the spectrum is periodic, an appropriate distribution is the circular von
Mises distribution that can parameterize the entire range of prior certainty of
the frequencies. An efficient alternating projections method is used to solve
the resulting optimization problem. The estimator is evaluated numerically and
compared with other estimators and the Cram\'er-Rao bound.
