Kalman Filter For Beginners With Matlab Examples Download Top Link

%% 2. KALMAN FILTER INITIALIZATION % State vector: [Position; Velocity] x_est = [0; 0]; % Initial guess: position 0, velocity 0 P_est = [100, 0; % High uncertainty in initial position 0, 10]; % Lower uncertainty in initial velocity

% Storage for results stored_x = zeros(2, N); stored_P = zeros(2, 2, N); Velocity] x_est = [0

%% 1. SIMULATE THE REAL WORLD dt = 0.1; % Time step (seconds) t = 0:dt:10; % Time vector (10 seconds) N = length(t); % Number of time steps % Initial guess: position 0

for k = 1:N true_pos(k) = true_vel * t(k); end velocity 0 P_est = [100