# Is EKF(robot_localization) expected to converge when the input data is relative like imu+odom

Hello, I am using the EKF node from the robot_localization package for local state estimation (odom->base_link), for which I am using the data from an IMU and wheel odometry, No matter how much I tune the Q matrix, the error estimate covariance matrix diagonal elements/variances keep on increasing slowly. Smaller the values of Q, the slower the values of P increase. Is this normal when using relative measurement data? OR should the EKF P matrix converge even when the input data is relative, considering the Q and R and tuned properly.

```
odom0_config: [false, false, false,
false, false, false,
true, true, false,
false, false, true,
false, false, false]
imu0_config: [false, false, false,
false, false, true,
false, false, false,
false, false, true,
true, false, false]
```

Thank You

You can at least configure the node to stop growing the variances when stopped with