基于船舶航行定位参数识别的数学模型设计

Research on mathematical model design based on ship navigation positioning parameter identification

为了利用最优参数提升船舶航行定位系统的运行性能,设计基于船舶航行定位参数识别的数学模型。构建描述船舶航行运动的大地坐标系和随船坐标系,利用2个坐标系的转换构建船舶航行定位系统的非线性运动方程。依据所构建的运动方程,利用无迹卡尔曼滤波方法,设计船舶航行定位系统参数识别的数学模型。利用粒子群优化算法优化所设计模型,选取定位参数初始状态误差的协方差矩阵作为优化目标,通过更新粒子位置和速度,确定卡尔曼滤波算法的协方差矩阵,更新待识别参数的状态向量,输出船舶航行定位参数识别结果。实验结果表明,该模型可以实现船舶航行定位参数的识别,依据参数识别结果,保障船舶实际航行轨迹紧密跟随目标航行轨迹。

In order to improve the performance of ship navigation positioning system by using the optimal parameters,a mathematical model based on ship navigation positioning parameters identification is designed.The geodetic coordinate system and shipboard coordinate system are constructed,and the nonlinear motion equation of ship navigation positioning system is constructed by the conversion of the two coordinate systems.Based on the motion equation and the untracked Kalman filter method,the mathematical model of ship navigation positioning system parameter identification is designed.The particle swarm optimization algorithm was used to optimize the designed model,and the covariance matrix of the initial state errors of positioning parameters was selected as the optimization target.The covariance matrix of Kalman filter algorithm was determined by updating the particle position and velocity,and the state vector of parameters to be identified was updated to output the identification results of ship navigation positioning parameters.The experimental results show that the model can realize the identification of navigation positioning parameters of ships,and ensure that the actual navigation trajectory of ships closely follow the target navigation trajectory according to the identification results of parameters.