基于海上观测值的舰船导航信号滤波方法研究  

Research on ship navigation signal filtering method based on sea observations

作　　者：叶祖超[1] 马欣 YE Zuchao;MA Xin(Beihai Marine Environmental Monitoring Center Station of Oceanic Administration,Beihai 536000,China)

机构地区：[1]国家海洋局北海海洋环境监测中心站,广西北海536000

出　　处：《舰船科学技术》2024年第19期113-117,共5页Ship Science and Technology

摘　　要：为弥补单一数据源不足,并在不同航行环境下,确保导航信号的稳定性与可靠性,研究基于海上观测值的舰船导航信号滤波方法。在舰船导航中,基于纬度、经度、海流分量、航速、航向和角速度变化量等观测值建立了导航信号模型。利用改进量子粒子群优化算法,优化卡尔曼滤波算法的观测噪声协方差矩阵,以及舰船导航信号模型噪声协方差矩阵,得到改进卡尔曼滤波算法,结合舰船导航信号模型,获取舰船导航信号滤波估计结果。实验结果证明,该方法可有效滤波估计舰船导航信号,提升舰船导航信号质量;该方法改进后的舰船导航轨迹与期望轨迹非常接近,即改进后该方法的舰船导航信号滤波效果较优。To compensate for the shortcomings of a single data source and ensure the stability and reliability of naviga-tion signals in different navigation environments,a ship navigation signal filtering method based on sea observation values is studied.In ship navigation,a navigation signal model is established based on observations such as latitude,longitude,ocean current components,speed,heading,and angular velocity changes.Using the improved quantum particle swarm optimiza-tion algorithm,the observation noise covariance matrix of the Kalman filtering algorithm and the noise covariance matrix of the ship navigation signal model are optimized to obtain the improved Kalman filtering algorithm.Combined with the ship navigation signal model,the filtering estimation results of the ship navigation signal are obtained.The experimental results demonstrate that this method can effectively filter and estimate ship navigation signals,improving the quality of ship naviga-tion signals;The improved ship navigation trajectory of this method is very close to the expected trajectory,indicating that the improved ship navigation signal filtering effect of this method is better.

关 键 词：海上观测值 舰船导航信号 滤波方法 量子粒子群 噪声协方差 卡尔曼滤波 

分 类 号：TP666.11[自动化与计算机技术—控制理论与控制工程]