If the model is not linear the model must be linearized in some working point, which is used in the Extended Kalman Filter. Kalman Filtering The trajectory (system) matrix in the state-space is given by. The linear Kalman filter contains a built-in linear constant-velocity motion model. Constant velocity The role of the motion model is to project the state into the future within t. Here we use the transition matrix F from the ball tracking example discussed in class. constant filter = trackingKF creates a linear Kalman filter object for a discrete-time, 2-D, constant-velocity moving object. Data is extracted from GPS and Accelerometer using mobile phone. The state is expected to be Cartesian state. 3 . models in matlab; Efficient approximative multiplication of square matrices in matlab; Sudoku solver in matlab; Xls2struct in matlab The state is expected to be Cartesian state. The most common dynamic model is a constant velocity (CV) model [1, 10], which assumes that the velocity is constant during a sampling interval. Extended Kalman Filters - MATLAB & Simulink - MathWorks 日本 The role of the motion model is to project the state into the future within t. Here we use the transition matrix F from the ball tracking example discussed in class. In this model: I am putting the following as my Measurement Covariance matrix: R = [r11, r12, 0, 0 ; r21, r22, 0, 0 ; 0, 0 , r33, r34 ;0, 0, r43, r44]; Sometimes I have my measurement Position (x',y') that is sometimes not so perfect. 3. Initial position of the target is x= [5000m 250 m/s 25000m 0m/s] T. Target starts to move with the position provided.