Kalman Filter For Beginners With Matlab | Examples Download

State = [position; velocity; acceleration]

% Plot results plot(0:dt:50, true_position, 'g-', 'LineWidth', 2); hold on; plot(0:dt:50, measurements, 'rx'); plot(0:dt:50, estimated_positions, 'b--', 'LineWidth', 2); legend('True', 'Noisy GPS', 'Kalman Estimate'); xlabel('Time (s)'); ylabel('Position (m)'); title('Kalman Filter for Constant Velocity'); grid on; kalman filter for beginners with matlab examples download

% Simulate t = 0:dt:5; true_pos = 100 + 0 t + 0.5 (-9.8)*t.^2; measurements = true_pos + sqrt(R)*randn(size(t)); State = [position; velocity; acceleration] % Plot results

% Generate true motion and noisy measurements true_position = 0:dt:50; measurements = true_position + sqrt(R)*randn(size(true_position)); State = [position

% Measurement noise (GPS error) R = 10;