Wang Zixuan, Liu Xixiang, Wu Xiaoqiang, Sheng Guangrun, Huang Yongjiang
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Rev Sci Instrum. 2022 Jun 1;93(6):065112. doi: 10.1063/5.0089117.
The integration of the strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) has become a basic navigation solution for Autonomous Underwater Vehicles (AUVs). However, DVL cannot obtain the velocity relative to the ground when the distance between the AUV and seabed is over the operating range, which occurs often when AUVs are sailing in the middle layer of the ocean. When the DVL velocity relative to the current is used for an integrated filter, the unknown current velocity is coupled with the measured velocity error, which decreases the positioning accuracy. To address this problem, the effect of unknown coupled current velocity is analyzed from the perspective of filter observability, and an integrated SINS/DVL/virtual velocity navigation method is proposed. The virtual velocity based on the velocity variation extracted from the inertial measurement unit and DVL is constructed and used as an aided measurement for the Kalman filter. With the help of virtual velocity, the current velocity can be easily decoupled from measured SINS velocity error. The results of simulation and experiments demonstrated that the proposed method can effectively improve both the convergence speed and accuracy of velocity error compared with the classical method with SINS/DVL integration and, thus, significantly improve the positioning accuracy.
捷联惯性导航系统（SINS）与多普勒速度计（DVL）的集成已成为自主水下航行器（AUV）的一种基本导航解决方案。然而，当AUV与海床之间的距离超过工作范围时，DVL无法获得相对于地面的速度，这种情况在AUV在海洋中层航行时经常发生。当将DVL相对于水流的速度用于组合滤波器时，未知的水流速度与测量的速度误差相耦合，这会降低定位精度。为了解决这个问题，从滤波器可观测性的角度分析了未知耦合水流速度的影响，并提出了一种SINS/DVL/虚拟速度组合导航方法。基于从惯性测量单元和DVL提取的速度变化构建虚拟速度，并将其用作卡尔曼滤波器的辅助测量。借助虚拟速度，可以很容易地将水流速度与测量的SINS速度误差解耦。仿真和实验结果表明，与经典的SINS/DVL组合方法相比，该方法能够有效提高速度误差的收敛速度和精度，从而显著提高定位精度。
