潜航器轨迹跟踪与航向预测算法

Research on Submarine Trajectory Tracking and Heading Prediction Algorithm

海况条件较差时,基于水下单点GPS定位系统的潜航器实时定位有较大测量误差,不利于潜航器的轨迹跟踪与航向预测。针对误差服从高斯分布的水下单点GPS定位系统,提出基于改进型扩展卡尔曼滤波算法的GPS跟踪方法和基于回归分析算法的航向预测方法。通过测试与仿真,对定位设备采集到的数据进行对比分析,试验结果表明,上述算法显著提高了轨迹测量精度与航向跟踪能力,准确绘制出了潜航器的实时航行轨迹与航向预测线,可应用于潜航器的轨迹跟踪项目中。

When the conditions of the sea condition are poor,the submersible based on underwater single point GPS positioning system has large measurement error in real-time positioning,which is unfavorable to the trajectory tracking and heading prediction of the submersible.Aiming at the underwater single-point GPS positioning system with Gaussian distribution error,a GPS tracking method based on improved extended Kalman filter algorithm and a heading prediction method based on regression analysis algorithm are proposed.Through the test and simulation,the data collected by the positioning device is compared and analyzed.The experimental results show that the above algorithm significantly improves the trajectory measurement accuracy and heading tracking ability,and accurately plots the real-time navigation trajectory and heading prediction line of the submersible,it can be applied to the trajectory tracking project of the submersible.