应用扩展卡尔曼滤波算法的船舶运动模型参数辨识

Parameter identification to motion model of ship by extended Kalman filter

为确定船舶运动模型中的未知参数,提出1种以增广的状态方程和扩展卡尔曼滤波算法进行船舶运动模型参数辨识的算法,并设计辨识实验.在辨识实验中,采用固定区间卡尔曼平滑算法进行数据预处理,用辨识实验结果确立船舶运动模型.仿真验证实验表明,用该方法确立的模型是可靠的.

In order to determine the unknown parameters in motion model of ship, a parameter identification algorithm using extended state equations and extended Kalman filter is proposed and the identification experiment is designed. Fixed interval Kalman smoothing algorithms are used for the test data pre-processing during the experiment and a mathematical model of ship motion is established by the experimental results. The simulation validation shows the model established by this approach is reliable.