For a beginner, the Kalman Filter has two steps: and Update .
% Define the process noise covariance Q = [0.01 0; 0 0.01]; For a beginner, the Kalman Filter has two steps: and Update
% Generate true positions true_pos = real_position + real_velocity * t; For a beginner
%% Simulation parameters dt = 0.01; % 10 ms time step t_end = 2; % 2 seconds of fall t = 0:dt:t_end; N = length(t); g = -9.81; % Gravity (m/s^2) %% Simulation parameters dt = 0.01
Forgetting that real systems are non-linear. Fix: Learn the Extended Kalman Filter (EKF) after mastering the linear KF.