机器学习算法的船舶路径跟踪误差估计

Estimation of ship path tracking error based on machine learning algorithm

路径跟踪是船舶航行过程中的一项关键技术,当前船舶路径跟踪的误差大,跟踪实时差,针对该难题,提出基于机器学习算法的船舶路径跟踪误差估计方法。首先对船舶路径跟踪的流程进行分析,找到引起船舶路径跟踪误差的原因,然后收集船舶路径跟踪误差的样本数据,采用机器学习算法建立船舶路径跟踪估计方法,最后对船舶路径跟踪进行仿真模拟测试。机器学习算法可以估计船舶路径跟踪误差变化特点,获得了高精度的船舶路径跟踪结果,减少了船舶路径跟踪误差,船舶路径跟踪实时更好,船舶路径跟踪结果的整体性要明显优于当前其他船舶路径跟踪误差估计方法,具有更加广泛的应用范围。

Path tracking is a key technology in the course of ship navigation. The current ship path tracking error is large and the real-time tracking is poor. Firstly, the process of ship path tracking is analyzed to find out the cause of ship path tracking error. Then, the sample data of ship path tracking error are collected, and the ship path tracking estimation method is established by machine learning algorithm. Finally, the ship path tracking is simulated and tested. Machine learning algorithm can estimate the variation characteristics of ship path tracking error, obtain high-precision ship path tracking results,reduce ship path tracking error, ship path tracking real-time is also good, the integrity of ship path tracking results is obviously better than other current ship path tracking error estimation methods, with A wider range of applications.