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% State Covariance Matrix (P) % Initial uncertainty about our guess. P = [1 0; 0 1]; Here’s a short, engaging story based on your
It’s a "smart averaging" technique that learns from past predictions and new measurements to filter out noise. Here’s a short
: A practical guide focusing on usage rather than complex statistical derivation Tutorial: The Kalman Filter (MIT) Here’s a short, engaging story based on your
% Velocity Plot subplot(2, 1, 2); plot(t, true_velocity, 'g', 'LineWidth', 2); hold on; plot(t, est_velocity, 'b-', 'LineWidth', 2); legend('True Velocity', 'Kalman Estimate'); xlabel('Time (s)'); ylabel('Velocity (m/s)'); title('Velocity