Kalman filter, defining the measurement model
Your observation are the $y_k$ your observation model is defined by $Y_k=HX_k+\eta_k$, where $\eta_k$ if a sample from a normal distribution.

If you want your kalman filter to estimate position, velocity and acceleration your state vector is : $X_k=[x_k,\dot{x}_k,\ddot{x}_k]^T$ and therefore your observation matrix is : $H=[0,0,1]$.

As stated by Rhei, your observations are what you get from the system at each time step, i.e. the measured acceleration.