动力定位中跟踪环境力突变的自适应无迹卡尔曼滤波

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.

An Adaptive Unscented Kalman Filter for Tracking Sudden Environmental Forces Changes in Dynamic Positioning System

Unscented Kalman filter was widely used in dynamic positioning system since it can re-construct unmeasured states as well as remove white and colored noise from the state estimates. This paper aims to solve the problem that unscented Kalman filter is unable to track sudden changes of the states of a vessel when it faces the extreme sea environment, while the dynamic positioning sys-tem requires to estimate these states accurately and instantaneously. By identifying the instant of a sudden change and appropriately adjusting the estimated covariance matrix, an adaptive unscented Kalman filter was proposed, which is able to track the states of vessel and reduce the deviation of the low-frequency position of the vessel efficiently. Numerical simulations show the effectiveness of the proposed scheme.