INS/USBL/DVL information fusion and fault-tolerant verification for underwater vehicles

Bo XU; Rui HAO; Chao WANG; Xun ZHANG; Jiao ZHANG

doi:10.3788/OPE.20172509.2508

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INS/USBL/DVL information fusion and fault-tolerant verification for underwater vehicles

Information Sciences | 更新时间：2020-08-13

- INS/USBL/DVL information fusion and fault-tolerant verification for underwater vehicles
- Optics and Precision Engineering Vol. 25, Issue 9, Pages: 2508-2515(2017)
- 作者机构：
  
  哈尔滨工程大学自动化学院, 黑龙江哈尔滨 150001
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20172509.2508
  CLC： U666.1
- Received：21 April 2017，
  
  Accepted：18 May 2017，
  
  Published：25 September 2017
- 稿件说明：
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Bo XU, Rui HAO, Chao WANG, et al. INS/USBL/DVL information fusion and fault-tolerant verification for underwater vehicles[J]. Optics and precision engineering, 2017, 25(9): 2508-2515.
DOI：

Bo XU, Rui HAO, Chao WANG, et al. INS/USBL/DVL information fusion and fault-tolerant verification for underwater vehicles[J]. Optics and precision engineering, 2017, 25(9): 2508-2515. DOI： 10.3788/OPE.20172509.2508.

摘要

针对水下潜航器惯导系统的定位误差积累和容错性差等问题，分析了水声超短基线的相位差定位方法，推导了基于惯导提供实时位置、姿态误差角信息的惯导/超短基线（INS/USBL）导航解算过程及其坐标转换。结合惯导/多普勒测速（INS/DVL）滤波器，给出INS/USBL/DVL组合导航联邦滤波在3种信息融合算法下的应用。通过MATLAB仿真对导航算法进行了验证，结果表明该导航算法能够抑制惯导系统误差随时间发散的问题，能充分利用了3种导航系统提供的参数信息，且状态维数低，滤波收敛速度快，其中基于精度因子信息分配方法的导航系统误差最小。容错性验证结果显示，当超短基线出现故障时，重构后的组合导航系统在较高航速情况下依旧能提供有效的导航参数。所提出的INS/USBL/DVL组合导航联邦滤波方法能够精确地提供水下潜航器的各位导航参数信息，且具有较高的容错性和稳定性。

Abstract

This paper focuses on the accumulated positioning errors and poorer fault tolerance of Inertial Navigation System(INS)in an underwater vehicle. The phase difference position of the underwater acoustic Ultra Short Base Line(USBL) was analyzed and the solution process and coordinate transformation of INS/USBL navigation was deduced based on real time positioning and attitude error angle information obtained by the INS. Finally

in combination of a INS/Doppler Velocity Log (INS/DVL)filter

the applications of the INS/USBL/DVL integrated navigation federation filtering in three kinds of information fusion algorithms. The fusion algorithm was verified by MATLAB simulation. The results demonstrate that algorithm is able to inhibit filtering divergence of INS. It makes the best of the parameter information obtained from three navigation system

and shows low state dimension and fast convergence speed. Among them

the navigation system based on precision factor has minimum system error. The fault tolerance verifies that the INS/USBL/DVL integrated navigation system still can provide effective navigation parameters at a higher navigation speed when the UBSL was broken. It concludes that the proposed INS/USBL/DVL integrated navigation federation filtering algorithm is able to provide navigation parameter information with high fault tolerance and stability for underwater vehicles effectively.

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references

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