摘要
水下机器人(autonomous underwater vehicle,AUV)导航定位精度一定上程度影响了AUV的工作效率,由于GNSS无法在水下使用,以捷联惯导系统/多普勒计程仪(SINS/DVL)的组合导航系统受到众多青睐。DVL在部分情况下会失效,若直接将DVL隔离,系统将变为纯惯性导航系统,严重影响导航定位的精度。为了应对DVL在部分波束缺失的情况,提出了一种DLinear-informer辅助组合导航算法。通过DLinear对原始输入数据特有的分解方式,增强了算法对AUV非线性信息的提取与学习,提高了速度预测精度。实验结果表明:所提算法能够准确预测DVL失效期间丢失波束的速度,降低组合导航的位置误差,提高了系统的鲁棒性和定位精度。
The navigation and positioning accuracy of an Autonomous Underwater Vehicle(AUV)affects the efficiency of the AUV to a certain extent,and since GNSS cannot be used underwater,the integrated navigation system of Strapdown Inertial Navigation System/Doppler Velocity Log(SINS/DVL)has been widely favored.However,DVL will fail in some cases,and if DVL is isolated directly,the system will become a pure inertial navigation system,which seriously affects the accuracy of navigation and positioning.In order to cope with the situation that DVL is missing in some beams,a DLinear-Informer assisted integrated navigation algorithm is proposed.Through DLinear's unique decomposition of the original input data,the algorithm enhances the extraction and learning of the nonlinear information of AUV and improves the velocity prediction accuracy.The experimental results show that the proposed algorithm can accurately predict the velocity of the lost beam during the DVL failure,reduce the position error of the integrated navigation,and improve the robustness and positioning accuracy of the system.
作者
匡兴红
黄傲威
Kuang Xinghong;Huang Aowei(College of Engineering Science and Technology,Shanghai Ocean University,Shanghai 201306,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2024年第8期1810-1822,共13页
Journal of System Simulation
