Jin Huang , Haoda Li , Zichen Liu , Zhikun Wang , Yingqiang Wang , Ying Chen
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引用次数: 0
摘要
综合导航系统(INS)集成了带式惯性导航系统(SINS)和多普勒速度记录仪(DVL),广泛应用于自主潜水器(AUV)的导航和定位。然而,由于 AUV 的尺寸和系统设计的限制,DVL 和 SINS 之间会出现坐标系不匹配的情况,这种不匹配可模拟为安装误差 (IE),包括安装误差角和杠杆臂误差,对系统的精度造成严重影响。为解决这些问题,我们引入了一种基于反馈误差状态卡尔曼滤波器(ESKF)的 INS,该 INS 考虑了 DVL 安装误差(IE),并提出了一种 DVL IE 补偿方法。本文详细介绍了基于 ESKF 的 INS 的系统设计,包括移动基座的粗初始对准、精细对准、机械化和数据融合。所提出的 IE 补偿方法旨在利用全球导航卫星系统(GNSS)进行观测,通过最小化误差模型输出来估算 IE 值,从而连续估算和修正 DVL IE。模拟和现场实验表明,补偿后的累积精度提高了 50.3%。最后,基于 ESKF 和 DVL IE 补偿的 INS 由圆盘形 AUV 搭载,在实际 AUV 导航应用中表现良好。
GNSS-aided installation error compensation for DVL/INS integrated navigation system using error-state Kalman filter
The integrated navigation system (INS), which integrates the strap-down inertial navigation system (SINS) and the Doppler velocity log (DVL), is widely used in the application of autonomous underwater vehicle (AUV) navigation and positioning. However, due to the constraints imposed by the AUV’s size and system design, a coordinate system mismatch occurs between the DVL and SINS, which can be modeled as installation error (IE), including installation error angles and lever arm errors that significantly impact the system’s accuracy. To address these issues, we introduce an INS based on feedback error-state Kalman filter (ESKF) that accounts for DVL installation error (IE) and propose a DVL IE compensation method. This paper details the system design of the ESKF-based INS, including the coarse initial alignment of the moving base, fine alignment, mechanization, and data fusion. The proposed IE compensation method is designed to successively estimate and correct the DVL IE, utilizing the global navigation satellite system (GNSS) for observations, minimizing the error model output to estimate the IE value. Simulations and field experiments indicate that the cumulative accuracy has been improved by 50.3% after compensation. Finally, carried by a disc-shaped AUV, the ESKF-based INS with DVL IE compensation performs well in practical AUV navigation applications.
期刊介绍:
Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.