Kalman Filter For Beginners With Matlab Examples Download Page
The Kalman filter gives a smooth estimate much closer to the true position than the raw noisy measurements. 5. MATLAB Example 2: Tracking a Falling Object (Acceleration) Now let’s track an object in free fall (constant acceleration due to gravity).
State = [position; velocity; acceleration]
% Generate true motion and noisy measurements true_position = 0:dt:50; measurements = true_position + sqrt(R)*randn(size(true_position));
The Kalman filter gives a smooth estimate much closer to the true position than the raw noisy measurements. 5. MATLAB Example 2: Tracking a Falling Object (Acceleration) Now let’s track an object in free fall (constant acceleration due to gravity).
State = [position; velocity; acceleration]
% Generate true motion and noisy measurements true_position = 0:dt:50; measurements = true_position + sqrt(R)*randn(size(true_position));