dx/dt = f(x,t) + W(t)
Where f() is your state space model, and W(t) is white noise process that represents the modeling errors/uncertainty in your state model. The process is the covariance of the stochastic processes W(t). You usually don't know W(t) exactly, which is why tuning kalman filter...