2-D Distance for Kalman measurements
I thought about it a bit more (power of posting), and decided the best way to scale $x$ and $\dot{x}$ is by the standard deviation, which is being tracked within the covariance matrix.

errX = (x_n - x_n-1)/sqrt(var(x));
errXdot = (xdot_n - xdot_n-1)/sqrt(var(xdot));
err2D = sqrt(errX^2 + errXdot^2);