测绘学报 ›› 2026, Vol. 55 ›› Issue (4): 698-707.doi: 10.11947/j.AGCS.2026.20260028

• 大地测量学与导航 • 上一篇    

顾及海冰漂移的浮标辅助UUV冰下组合导航方法

白思源(), 柴洪洲(), 吴庆, 李根, 叶宇浩, 马洪磊   

  1. 信息工程大学地理空间信息学院,河南 郑州 450001
  • 收稿日期:2026-02-05 修回日期:2026-04-09 发布日期:2026-05-11
  • 通讯作者: 柴洪洲 E-mail:baisiyuan_kyle@foxmail.com;chaihz1969@163.com
  • 作者简介:白思源(2000—),男,博士生,研究方向为UUV极区组合导航。 E-mail:baisiyuan_kyle@foxmail.com
  • 基金资助:
    国家自然科学基金(42404010; 42574011)

Buoys-aided integrated navigation method for UUV under ice with sea ice drift compensation

Siyuan BAI(), Hongzhou CHAI(), Qing WU, Gen LI, Yuhao YE, Honglei MA   

  1. Geography Space Information Institute, Information Engineering University, Zhengzhou 450001, China
  • Received:2026-02-05 Revised:2026-04-09 Published:2026-05-11
  • Contact: Hongzhou CHAI E-mail:baisiyuan_kyle@foxmail.com;chaihz1969@163.com
  • About author:BAI Siyuan (2000—), male, PhD candidate, majors in UUV polar region integrated navigation. E-mail: baisiyuan_kyle@foxmail.com
  • Supported by:
    The National Natural Science Foundation of China(42404010; 42574011)

摘要:

针对水下无人潜航器(UUV)冰下航行过程中,上视多普勒测速仪(DVL)测量值受海冰漂移影响明显的问题,本文提出一种基于冰基浮标辅助的UUV冰下组合导航方法。首先,建立海冰漂移运动模型,明确海冰漂移对UUV速度测量的耦合机制;然后,详细推导考虑海冰漂移的各传感器测量误差方程,分别构建了单浮标/双浮标辅助的UUV惯导/上视DVL组合导航Kalman滤波模型。最后,设计仿真试验,结果表明在单浮标辅助模式下,本文方法有效抑制了海冰漂移带来的系统误差,定位误差较忽略海冰漂移误差的捷联惯性导航系统/上视DVL传统组合导航方法降低了81.96%;双浮标辅助模式利用基线运动信息,可实现对海冰漂移误差的准确估计,定位误差较传统方法降低了93.29%,为UUV冰下长航时高精度导航提供了有效解决方案。

关键词: 海冰漂移, UUV, 冰下导航定位, 冰基浮标, 上视DVL, 卡尔曼滤波

Abstract:

To address the problem that the measurement values of the upward-looking Doppler velocity log (DVL) are significantly affected by sea ice drift when unmanned underwater vehicle (UUV) navigate under ice, a buoy-aided integrated navigation method for UUV under ice is proposed. Firstly, a sea ice drift motion model is established to clarify the coupling mechanism of sea ice drift on UUV velocity measurements. Secondly, the measurement error equations of each sensor considering sea ice drift are derived in detail, and the Kalman filter models for the UUV inertial navigation/upward-looking DVL integrated navigation assisted by single-buoysanddouble-buoysareconstructedrespectively. Finally, simulation experiments are designed. The results show that, in the single-buoy-aided mode, the proposed algorithm effectively suppresses the systematic errors induced by sea ice drift, achieving a positioning error reduction of 81.96% over the traditional SINS/upward-looking DVL integrated navigation method ignoring sea ice drift errors. In the dual-buoy-aided mode, by leveraging baseline motion information, the algorithm enables accurate estimation of sea ice drift errors, further reducing positioning error by 93.29% compared to traditional method. This provides an effective solution for long-endurance, high-precision UUV navigation under ice.

Key words: sea ice drift, unmanned underwater vehicle, under-ice navigation and positioning, ice-based buoy, upward-looking DVL, Kalman filter

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