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无迹卡尔曼滤波可以在状态估计中滤去噪声干扰,已经被广泛应用于动力定位系统中。针对复杂海洋情况下动力定位系统需要准确、及时地估计当前时刻的状态而无迹卡尔曼滤波无法跟踪状态突变的问题,为此文章提出了一种自适应无迹卡尔曼滤波。通过及时判断状态值突变并适当调整后验均方差矩阵,可有效地跟踪船舶状态并减小实际位置与定点位置的偏差。仿真实验证明了算法的有效性。
Unsupervised Kalman filtering can filter out noise interference in the state estimation and has been widely used in dynamic positioning system. In order to solve the problem of dynamical locating system in complicated ocean situation, it is necessary to estimate the state of the current moment accurately and timely, and the unscented Kalman filter can not track the state mutation. In this paper, an adaptive unscented Kalman filter is proposed. By judging the abrupt change of state value in time and adjusting the posterior mean square error matrix, the state of the ship can be effectively tracked and the deviation between the actual location and the fixed location can be reduced. Simulation experiments show the effectiveness of the algorithm.