--- Kalman Filter For Beginners With Matlab Examples Best Instant

x_est = x_pred + K * y; P = (eye(2) - K * H) * P_pred;

%% Visualizing Kalman Gain and Uncertainty clear; clc; dt = 0.1; F = [1 dt; 0 1]; H = [1 0]; R = 9; % Measurement noise variance Q = [0.1 0; 0 0.1]; --- Kalman Filter For Beginners With MATLAB Examples BEST

for k = 1:50 % Predict x_pred = F * x_est; P_pred = F * P * F' + Q; x_est = x_pred + K * y; P

figure; subplot(2,1,1); plot(1:50, K_history, 'b-', 'LineWidth', 2); xlabel('Time Step'); ylabel('Kalman Gain (Position)'); title('Kalman Gain Convergence'); grid on; dt = 0.1