This template is suitable to do a tiny programming task: Implementing a linear Kalman filter.
Here the data of a GPS sensor is provided.
Open the template and run it, e.g. in Octave by pressing F5. Have a look at the output of the data. This plot shows the noisy data from the GPS sensor.
Implement the linear Kalman filter, so the trajectory of the robot. Plot the output in the same plot, which is already prepared in the template.
Plot the estimated velocity of the robot, as well as the values in the covariance matrix. Notice how these values change over time.
Comment in the if condition in the file generate_noisy_data.m. With this added, the path of the robot changes after half the distance. Use the system noise matrix and find suitable values.