I am working on implementing a Kalman filter for position and velocity estimation of a quadcopter using IMU and vision. First I am trying to use the IMU to get position and velocity. In a tutorial [1] the process model for velocity estimation using IMU sensor data is based on Newton's equation of motion
$$ v = u + at \\ \\ \begin{bmatrix} \dot{x} \\ \dot{y} \\ \dot{z} \end{bmatrix}_{k+1} = \begin{bmatrix} \dot{x} \\ \dot{y} \\ \dot{z} \end{bmatrix}_{k} + \begin{bmatrix} \ddot{x} \\ \ddot{y} \\ \ddot{z} \end{bmatrix}_k \Delta T $$
while in the paper [2] the process model uses angular rates along with acceleration to propagate the linear velocity based on the below set of equations.
$$ \begin{bmatrix} u \\ v \\ w \\ \end{bmatrix}_{k+1} = \begin{bmatrix} u \\ v \\ w \\ \end{bmatrix}_{k} + \begin{bmatrix} 0& r& -q \\ -r& 0& p \\ -p& q& 0 \end{bmatrix} \begin{bmatrix} u \\ v \\ w \\ \end{bmatrix}_{k} \Delta T+ \begin{bmatrix} a_x \\ a_y \\ a_z \\ \end{bmatrix}_{k} \Delta T + \begin{bmatrix} g_x \\ g_y \\ g_z \\ \end{bmatrix}_{k} \Delta T $$
where u, v, w are the linear velocities | p, q, r are the gyro rates while a_x,a_y,a_z are the acceleration | g_x,g_y,g_z are the gravity vector
Why do we have two different ways of calculating linear velocities? Which one of these methods should I use when modeling a quadcopter UAV motion?
[1] http://campar.in.tum.de/Chair/KalmanFilter
[2] Shiau, et al. Unscented Kalman Filtering for Attitude Determination Using Mems Sensors Tamkang Journal of Science and Engineering, Tamkang University, 2013, 16, 165-176