基于卡尔曼滤波算法船舶AIS轨迹估计研究

AIS是集船舶导航、避碰、海事监管于一体的现代化无线电系统,在水上交通运输领域里发挥着重要作用。为了弥补AIS数据堵塞等原因导致更新数据不及时,造成船舶轨迹的不准确或者误差较大的问题,提出利用对卡尔曼滤波算法进行适当的修改,引入系统噪声和测量噪声,利用AIS船舶观测节点数据对系统状态做最小二乘法估计,对船舶运动轨迹进行平滑和预测,并对不同时间段可靠性误差进行分析,能够比较正确地估计出船舶轨迹。

Research on estimation of AIS vessel trajectory data based on Kalman filter algorithm

Automatic Identification System（AIS）is a modern radio system integrates vessel navigation,collision avoidance and maritime supervision,which plays an important role in the field of water transportation. In order to compensate the inaccuracy of vessel trajectory caused by untimely data updating due to data blockage in transmitting,it is proposed that the Kalman filter algorithm should be properly modified,the system noise and measurement noise is introduced. The vessel trajectory is smoothed and predicted with least square method by using the recorded AIS vessel observation node data. The reliability error of different time period is analyzed. The experiment result shows that this method can predict the vessel trajectory correctly.