  In the present work, we consider a stable one-dimensional gaussian
autoregressive model in continous time. Using the limit theorems with
logarithmic averaging obtained for continous local martingales, we construct
then an estimator of the noise covariance $\sigma^{2}$ and an estimator of
$\theta$ different of the one of the least squares estimator. By exploiting the
weighting method we ameliorate the convergence rates of these new estimators.
