I've recently implemented a kalman filter to estimate altitude for a small robot with an IMU+Baro sensor mounted on it.
My objective is to get max precision I can have, using this two sensor, with small computing power that a MCU can provide me. I've tuned my filter and it seems to work pretty well.
Can I obtain a significant improvement using an Extended Kalman Filter instead of a normal Kalman Filter and if it worth time to implement it?
More in detail, since this request is too specific for each application, if a Model function that use Baro and Accel as states should be linearized and used in a EKF and if this can improve data reliability compared to a simply KF?