电子学报 ›› 2022, Vol. 50 ›› Issue (4): 811-822.DOI: 10.12263/DZXB.20211167

• 智能时空信息服务技术 • 上一篇    下一篇

GNSS拒止环境下的伪卫星指纹定位方法

黄璐1,2, 蔚保国2, 李宏生1, 李隽2, 贾浩男1,2, 程建强2, 李雅宁1,2   

  1. 1.东南大学仪器科学与工程学院微惯性仪表与先进导航技术教育部重点实验室,江苏 南京 210096
    2.卫星导航系统与装备技术国家重点实验室,河北 石家庄 050081
  • 收稿日期:2021-08-28 修回日期:2022-01-17 出版日期:2022-04-25 发布日期:2022-04-25
  • 作者简介:黄 璐 男,1991年2月出生,辽宁盘锦人.2017年硕士毕业于哈尔滨工程大学信息与通信工程专业.2019年于东南大学仪器科学与工程专业攻读博士学位.中国电子学会会员.现就职于中国电科54所卫星导航系统与装备技术国家重点实验室.主要研究方向为导航、定位技术及位置服务.E-mail: hlcetc54@163.com
    蔚保国 男,1966年10月出生,内蒙古凉城人.1988年毕业于国防科技大学电子工程系.博士生导师,中国电科集团首席科学家,中国电科54所副总工程师,卫星导航系统与装备技术国家重点实验室主任,中国卫星导航重大专项体系总体专家组专家,中国卫星导航定位协会室内导航定位专委会主任委员.主要研究方向为北斗卫星导航系统与综合PNT技术.
    李宏生(通讯作者) 男,1964年8月出生,江苏泰州人.1995年毕业于东南大学仪器科学与工程学院.1995—1997年于华中科技大学攻读博士后.1997年进入东南大学仪器科学与工程学院任教,现为教授、博士生导师.主要研究方向为惯性仪表与惯性导航技术,微机电系统(MEMS)技术.
  • 基金资助:
    国家重点研发计划项目(2021YFB3900800)

Pseudolite Fingerprint Positioning Method under GNSS Rejection Environment

HUANG Lu1,2, YU Bao-guo2, LI Hong-sheng1, LI Jun2, JIA Hao-nan1,2, CHENG Jian-qiang2, LI Ya-ning1,2   

  1. 1.Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology,Ministry of Education,School of Instrument Science and Engineering,Southeast University,Nanjing,Jiangsu 210096,China.
    2.State Key Laboratory of Satellite Navigation System and Equipment Technology,Shijiazhang,Hebei 050081,China
  • Received:2021-08-28 Revised:2022-01-17 Online:2022-04-25 Published:2022-04-25

摘要:

伪卫星具有发射与天上卫星相同信号的能力,可以作为GNSS(Global Navigation Satellite System)信号遮挡环境下稳定可靠的定位信号源,使得基于现有终端硬件条件实现室外内连续高精度定位成为可能,因此逐渐成为室内定位领域的研究热点.本文提出了一种基于同源多通道伪卫星的指纹库匹配定位方法,利用顾及位置信息的变分自编码网络(Variational Auto-Encoder,VAE)学习伪卫星载波相位信息在隐含空间下的概率分布特征,建立伪卫星观测数据隐含特征与室内位置间的映射关系,进而实现GNSS拒止环境下的指纹匹配定位.针对指纹定位结果波动大的问题,本文提出一种粒子滤波融合处理方法,提高了定位系统的稳定性和定位精度.本文在试验环境以及机场环境下,通过大量试验验证了该定位算法在动态和静态下的定位性能,并与常用的基于指纹库匹配的定位方法进行了比较.结果表明,在室内试验环境下,动态平均定位精度为0.39 m,95%的定位误差小于0.85 m,在真实机场环境下,动态平均定位精度为0.75 m,最大定位误差为1.69 m,92%的定位误差小于1 m,验证了算法的有效性.

关键词: 伪卫星, 载波相位, 室内定位, 指纹匹配, 机器学习

Abstract:

Pseudolites have the ability to transmit the same signals as GNSS(Global Navigation Satellite System) satellites, and can provide stable and reliable positioning signals for the navigation signal obstructed environment, making it possible to achieve continuous high-precision positioning outdoors based on the existing terminal hardware conditions. Therefore, it has gradually become a research hotspot in the field of indoor positioning. In this paper, a fingerprint database matching and positioning method based on homologous multi-channel pseudolites is proposed. The variational autoencoder network that takes into account the position information is designed to learn the probability distribution characteristics of the pseudolite carrier phase information in the hidden space. Then, the mapping relationship between the hidden features of the pseudolite observation data and the indoor location is established. After this, aiming at the problem of large fluctuation of fingerprint location results, a particle filter fusion processing method is proposed to improve the stability and accuracy of the location system. In the experimental environment and airport environment, a large number of experiments verify the positioning performance of the positioning algorithm under dynamic and static conditions, and compare it with the common positioning methods based on fingerprint database matching. The results show that the dynamic average positioning accuracy is 0.39 m in the indoor test environment, and 95% of the positioning error is better than 0.85 m. In the real airport environment, the dynamic average positioning accuracy is 0.75 m, the maximum positioning error is 1.69 m, and 92% of the positioning error is better than 1m. The effectiveness of the algorithm is verified.

Key words: pseudolite, carrier phase, indoor positioning, fingerprint matching, machine learning

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