rmse_raw = sqrt(mean((measurements - true_pos).^2)); rmse_kalman = sqrt(mean((stored_x(1,:) - true_pos).^2)); fprintf('Raw sensor RMSE: %.3f m\n', rmse_raw); fprintf('Kalman filter RMSE: %.3f m\n', rmse_kalman);
In this example, we use the logic but simplified—because gravity is a known input. rmse_raw = sqrt(mean((measurements - true_pos)
%% Kalman Filter x_est = [0; 0]; % [pos; vel] P_est = eye(2) * 1; rmse_raw = sqrt(mean((measurements - true_pos).^2))
git clone https://github.com/balzer82/Kalman MATLAB.zip If you are an instructor, create a ZIP of the above scripts and host it. Here is a simple batch script (Windows) or bash (Mac/Linux) to create a zip: rmse_kalman = sqrt(mean((stored_x(1
stored_x = zeros(2, N);
%% 4. PLOT RESULTS figure('Position', [100, 100, 800, 600]);