A maneuvering target tracking algorithm based on UKF-Singer

Singer model is a whole statistic model, which considers all the possibility of the variance of the maneuvering target, and it is fit for a variety of situations and many kinds of maneuvers. So the probability of the occurrence of the concrete maneuver in each concrete tactics situation is small, which leads to the low accuracy of tracking. The UKF(unscented Kalman filter)-Singer algorithm uses a lot of sigma points which approach the status of the system, using unscented transformation, to get the filter value based on the update of the status equation. It efficiently solves the problem which lies in the traditional Singer model and improves the tracking accuracy. The algorithm is proved efficient through simulation tests.