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弹箭与制导学报 >

2022 , Vol. 42 >Issue 5: 1 - 5

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2022.05.001

Elman网络辅助SINS/GNSS组合导航方法研究

  • 张琨 ,
  • 程玉 ,
  • 吴有龙 ,
  • 陈帅 ,
  • 白钲皓
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  • 南京理工大学自动化学院,南京 210094

张琨(2000—),男,安徽六安人,硕士研究生,研究方向:惯性导航、组合导航。

收稿日期: 2022-04-20

  网络出版日期: 2025-01-16

基金资助

江苏省博士后科研资助基金(2021K463C)

江苏省高等学校自然科学研究面上项目(19KJB510028)

国防基础科研计划项目(WDZC20190303)

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Elman Network Aided SINS/GNSS Integrated Navigation

  • ZHANG Kun ,
  • CHENG Yu ,
  • WU Youlong ,
  • CHEN Shuai ,
  • BAI Zhenghao
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  • School of Automation, Nanjing University of Science and Technology,Nanjing 210094,China

Received date: 2022-04-20

  Online published: 2025-01-16

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摘要

针对SINS/GNSS组合导航系统在GNSS信号失锁情况下定位误差迅速增大问题。提出一种基于Elman神经网络和自适应卡尔曼滤波的SINS/GNSS伪松组合导航方法。在GNSS信号可用时,利用SINS,GNSS数据训练Elman神经网络;当GNSS失锁时,利用训练好的网络模型预测GNSS观测值,保证组合导航的连续性。实验表明:GNSS信号失锁约3 min,该方法水平定位精度相较于纯惯导提高了64%,有效提高了纯惯导的定位精度。

关键词： 神经网络; 组合导航; 自适应卡尔曼滤波; 误差发散

本文引用格式

张琨 , 程玉 , 吴有龙 , 陈帅 , 白钲皓 . Elman网络辅助SINS/GNSS组合导航方法研究[J]. 弹箭与制导学报, 2022 , 42(5) : 1 -5 . DOI: 10.15892/j.cnki.djzdxb.2022.05.001

Abstract

In the SINS/GNSS integrated navigation system, the position error of pure inertial navigation will increase rapidly during GNSS outages. A method based on Elman neural network and adaptive Kalman filter to improve SINS/GNSS pseudo-loose integrated navigation is proposed. When GNSS signal is available, Elman neural network is trained by SINS and GNSS data. When the GNSS outage occurs, the trained network model is used to predict the GNSS observations to ensure the continuity of integrated navigation. Experiment showed that the horizontal position accuracy of the proposed method was 64% higher than that of the pure inertial navigation system when the GNSS signal was lost for about 3 min. The position accuracy of the pure inertial navigation system is effectively improved.

Key words： neural network; integrated navigation; adaptive Kalman filter; error divergence

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