Let's consider a simple example where we want to estimate the position and velocity of an object from noisy measurements of its position.

In this guide, we've introduced the basics of the Kalman filter and provided MATLAB examples to help you get started. The Kalman filter is a powerful tool for estimating the state of a system from noisy measurements, and it has a wide range of applications in navigation, control systems, and signal processing.

% Plot the results plot(t, x_true, 'b', t, x_est(1, :), 'r'); xlabel('Time'); ylabel('Position'); legend('True', 'Estimated');