水下重力匹配导航的非线性滤波算法研究

Research on Nonlinear Filtering Algorithm for UnderwaterGravity Matching Navigation

地球重力场辅助惯性导航系统应用于水下运载体的导航定位,能够有效降低惯性导航系统误差随时间累积的影响,保证水下运载体的长时间导航精度。EKF算法与UKF算法是两种常用的非线性滤波算法,以水下重力匹配导航为例,在南海选取两块重力异常变化剧烈程度不同的海域开展仿真试验,试验结果表明:两种算法都能够匹配真实航迹,有效降低惯导定位误差,采用UKF算法的导航定位精度水平较EKF算法提升30%以上,具有较好的精度提高作用。

The earth gravity field-assisted inertial navigation system is applied to the navigation and positioning of underwater vehicles,which can effectively reduce the influence of inertial navigation system errors accumulated over time and ensure the long-term naviga-tion accuracy of underwater vehicles.The EKF algorithm and UKF algorithm are two commonly used nonlinear filtering algorithms.Taking underwater gravity matching navigation as an example,two sea areas with different gravity anomalies are selected to carry out simulation tests in the South China Sea.The experimental results show that:both algorithms can match the real track and effectively reduce the inertial navigation positioning error.The navigation and positioning accuracy of the UKF algorithm is higher than that of the EKF algorithm.It is improved by more than 30%,which has a good effect of improving accuracy.