基于IEKF的水下无人潜器无源动基座自对准方法  

Passive self-alignment method based on IEKF for moving base of AUV

作　　者：黄凤荣 邢路然 陈英姝[1] 王震[1] 朱雨晨 HUANG Fengrong;XING Luran;CHEN Yingshu;WANG Zhen;ZHU Yuchen(School of Mechanical Engineering,Hebei University of Technology,Tianjin 300401,China)

机构地区：[1]河北工业大学机械工程学院,天津300401

出　　处：《中国惯性技术学报》2021年第1期23-27,34,共6页Journal of Chinese Inertial Technology

基　　金：国家自然科学基金(61973333)。

摘　　要：针对水下无人潜器无准确外参考信息条件下惯导系统动基座自对准问题,提出基于不变扩展卡尔曼滤波(IEKF)的动基座自对准方法。首先,建立系统误差模型,并针对系统动态模型的不确定性,设计自对准的不变扩展卡尔曼滤波算法;同时基于水下无人潜器一般工作在匀速运动状态,将航向信息耦合到自对准滤波器的量测方程中,最终实现了无准确速度信息条件下的动基座初始对准。跑车实验证明,提出的方法在大失准角情况下,航向角在30 min内收敛到惯性元件所对应的航向精度水平。证明了所提出方法的有效性和可行性。该方法增强了水下和陆上惯性导航设备初始对准的环境适应性。A self-alignment method based on invariant extended Kalman filter(IEKF)is proposed for autonomous underwater vehicle(AUV)self-alignment on moving base without accurate external reference information.Firstly,the system error model is established,and the self-aligning IEKF algorithm is designed for the uncertainty of the system dynamic model.At the same time,the heading information is coupled to the measurement equation of the self-aligning filter based on the fact that the AUV works in the state of uniform motion.Finally,the initial alignment of moving base without initial heading angle information and accurate velocity information is realized.Experiments show that the heading angle of the proposed method converges to the corresponding heading accuracy level of inertial component in 30 min under the condition of large misalignment angle,which proves the effectiveness and feasibility of the method.The proposed method can be widely used in underwater and land-based alignment environment with similar initial alignment conditions,and can enhance the environmental adaptation of inertial navigation equipment.

关 键 词：无源自主导航 不变扩展卡尔曼滤波 大失准角 快速对准 

分 类 号：U666.1[交通运输工程—船舶及航道工程]