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% Initialize the state and covariance x0 = [0; 0]; % initial state P0 = [1 0; 0 1]; % initial covariance
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');
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