How Are Unmeasured Properties (Velocity and Covariance of Velocity) Handled with a Kalman Filter?
This is exactly where the Dynamic Model comes into play.
The whole idea of the Kalman Filter is that you have a model which connects between variables which are measured to those which are not measured (Estimation) or measured differently (Fusion).
Since the velocity is the derivative of the location over time you have a model which connects them both. Once you set the model (Piece Wise Constant Velocity / Changing Velocity and the level of noise) the Kalman Filter does the fusion of the data and the model to estimate the parameters.