In various fields, the {\it signal} process, whose law depends on an unknown parameter $artheta \in \Theta \subset \R^p$, can not be observed directly but only through an {\it observation} process. We will talk about the so called fractional partial observation setting, where the observation process $Y=\left( Y_t, t \geq 0 ight)$ is given by a stochastic differential equation: egin{equation} \label{mod:modelgeneral} Y_t = Y_0 + \int_0^t h(X_s, artheta) ds + \sigma W^H_t\,, \quad t > 0 \end{equation} where the function $ h: \, \R imes \Theta \longrightarrow \R$ and the constant $\sigma>0$ are known and the noise $\left( W^H_t\,, t\geq 0 ight)$ is a fractional Brownian motion valued in $\R$ independent of the signal process $X$ and the initial condition $Y_0$. In this setting, the estimation of the unknown parameter $artheta \in \Theta$ given the observation of the continuous sample path $Y^T=\left( Y_t , 0 \leq t \leq T ight)$, $T>0$, naturally arises.