EKF partial state update question

This is a follow up to

Maintaining positive-definite property for covariance in an unscented Kalman filter update

...but it's deserving of its own question, I think.

I am processing measurements in my EKF for a subset of the variables in my state. My state vector is of cardinality 12. I am directly measuring my state variables, which means my state-to-measurement function $h$ is the identity. I am trying to update the first two variables in my state vector, which are the x and y position of my robot. My Kalman update matrices currently look like this:

State $x$ (just test values): $$\left(\begin{array}{ccc} 0.4018 & 0.0760 \end{array} \right)$$

Covariance matrix $P$ (pulled from log file): $$\left(\begin{array}{ccc} 0.1015 & -0.0137 & -0.2900 & 0 & 0 & 0 & 0.0195 & 0.0233 & 0.1004 & 0 & 0 & 0 \\ -0.0137 & 0.5825 & -0.0107 & 0 & 0 & 0 & 0.0002 & -0.7626 & -0.0165 & 0 & 0 & 0 \\ -0.2900 & -0.0107 & 9.6257 & 0 & 0 & 0 & 0.0015 & 0.0778 & -2.9359 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0.0100 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0.0100 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0.0100 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0.0195 & 0.0002 & 0.0015 & 0 & 0 & 0 & 0.0100 & 0 & 0 & 0 & 0 & 0 \\ 0.0233 & -0.7626 & 0.0778 & 0 & 0 & 0 & 0 & 1.0000 & 0 & 0 & 0 & 0 \\ 0.1004 & -0.0165 & -2.9359 & 0 & 0 & 0 & 0 & 0 & 1.0000 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.0100 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.0100 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.0100 \\ \end{array} \right)$$

Measurement $z$ (just test values): $$\left(\begin{array}{ccc} 2 & 2 \end{array} \right)$$

"Jacobean" $J$: $$\left(\begin{array}{ccc} 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \end{array} \right)$$

Measurement covariance $R$ (just test values): $$\left(\begin{array}{ccc} 5 & 0 \\ 0 & 5 \\ \end{array} \right)$$

Kalman gain $K = PJ^T(JPJ^T + R)^{-1}$:

$$\left(\begin{array}{ccc} 0.0199 & -0.0024 \\ -0.0024 & 0.1043 \\ -0.0569 & -0.0021 \\ 0 & 0 \\ 0 & 0 \\ 0 & 0 \\ 0.0038 & 0.0000 \\ 0.0042 & -0.1366 \\ 0.0197 & -0.0029 \\ 0 & 0 \\ 0 & 0 \\ 0 & 0 \\ \end{array} \right)$$

$K$ is 12x2, meaning that my innovation - and therefore both measurement and current state - would need to be 2x1 in order to have a 12x1 result to add to the current full state:

$x' = x + K(z - h(x_s))$

where $x_s$ is a vector containing only the parts of the full state vector that I am measuring.

Here's my question: $K(z - h(x_s))$ yields

$$\left(\begin{array}{ccc} 0.0272 \\ 0.1969 \\ -0.0948 \\ 0 \\ 0 \\ 0 \\ 0.0062 \\ -0.2561 \\ 0.0258 \\ 0 \\ 0 \\ 0 \\ \end{array} \right)$$

Does it make sense that this vector, which I will add to the current state, has non-zero values in positions other that 1 and 2 (the x and y positions of my robot)? The other non-zero locations correspond to the robot's z location, and the x, y, and z velocities. It seems strange to me that a measurement of x and y should yield changes to other variables in the state vector. Am I incorrect in this assumption?

Incidentally, the covariance update works very well with the Jacobean in this form, and maintains its positive-definite property.