• 中国科学引文数据库(CSCD)
  • 中文科技期刊数据库
  • 中国核心期刊(遴选)数据库
  • 日本科学技术振兴机构数据库(JST)
  • 中国学术期刊(网络版)(CNKI)
  • 中国学术期刊综合评价数据库(CAJCED)
  • 中国超星期刊域出版平台

基于EMD-LSTM耦合预测模型的BDS多路径误差削弱方法研究

徐小汶, 陶 远

徐小汶, 陶 远. 基于EMD-LSTM耦合预测模型的BDS多路径误差削弱方法研究[J]. 全球定位系统, 2020, 45(2): 98-104. DOI: DOI:10.13442/j.gnss.1008-9268.2020.02.016
引用本文: 徐小汶, 陶 远. 基于EMD-LSTM耦合预测模型的BDS多路径误差削弱方法研究[J]. 全球定位系统, 2020, 45(2): 98-104. DOI: DOI:10.13442/j.gnss.1008-9268.2020.02.016
XU Xiaowen, TAO Yuan. BDS multipath errors reducing method based on EMD-LSTM coupled prediction model[J]. GNSS World of China, 2020, 45(2): 98-104. DOI: DOI:10.13442/j.gnss.1008-9268.2020.02.016
Citation: XU Xiaowen, TAO Yuan. BDS multipath errors reducing method based on EMD-LSTM coupled prediction model[J]. GNSS World of China, 2020, 45(2): 98-104. DOI: DOI:10.13442/j.gnss.1008-9268.2020.02.016

基于EMD-LSTM耦合预测模型的BDS多路径误差削弱方法研究

详细信息
    作者简介:

    徐小汶 (1991—),男,硕士,研究方向为GNSS卫星导航与定位.

    通信作者:

    徐小汶 E-mail:2399472552@qq.com

BDS multipath errors reducing method based on EMD-LSTM coupled prediction model

  • 摘要: 北斗卫星导航系统(BDS)在短基线测量中存在的多路径误差是影响定位精度的主要误差项. 针对多路径误差的非线性以及坐标序列的非平稳特性,拟采用经验模态分解(EMD)与长短期记忆网络(LSTM)结合的方法,构建EMD-LSTM耦合预测模型,对多路径误差进行预测,削弱多路径误差的影响. 实验结果表明,EMD-LSTM耦合预测模型能够有效地削弱了多路径误差影响,E、N、U方向精度分别提高了22%、36%、40%.
    Abstract: The multipath errors in short baseline measurement of BeiDou Navigation Satellite System (BDS) were the main errors affecting positioning accuracy. Aiming at the nonlinearity of multipath errors and the non-stationarity of coordinate series, a coupled prediction model of EMD-LSTM was proposed by combining empirical mode decomposition (EMD) with long short-term memory (LSTM) to predict multipath errors and weaken the influence of multipath errors. The experimental results show that the EMD-LSTM coupled prediction model can effectively reduce the multipath errors, and the E, N,and U directions were respectively improved by 22%, 36%, and 40%.
  • 钟萍, 丁晓利, 郑大伟, 等. 一种基于交叉证认技术的自适应小波变换及其在削减GPS多路径误差中的应用[J]. 测绘学报, 2007,36 (3):279-285.
    COMP C J, AXELRADP. An adaptive SNR-based carrier phase multipath mitigation technique[J]. IEEE transactions on aerospace andelectron systems, 1998, 34(1):264-276. DOI: 10.1109/7.640284.
    ZHANG Z T, LI B F, GAO Y, et al. Real-time carrier phase multipath detection based on dual-frequency C/N0 data[J]. GPS solutions, 2018, 23(1). DOI: 10.1007/s10291-018-0799-6.
    ZHENG D W, ZHONG P M, DING X L, et al. Filtering GPS time-series using a vondrak filter and crossvalidation[J]. Journal of geodesy, 2005, 79(6-7):363-369. DOI: 10.1007/s00190-005-0474-x.
    戴吾蛟, 丁晓利, 朱建军, 等. 基于经验模式分解的滤波去噪法及其在GPS多路径效应中的应用[J].测绘学报, 2006,35 (4):321-327.
    刘超, 王坚, 许长辉, 等. 基于经验模态分解的GPS/伪卫星组合基线解算模型[J].武汉大学学报(信息科学版), 2010, 35(8):996-1000.
    DAI W J, SHI Q, CAI C S. Characteristics of the BDS carrier phase multipath and its mitigation methods in relative positioning[J]. Sensors, 2017, 17(4):796. DOI: 10.3390/s17040796.
    ZHNAG Q Z, YANG W, ZHANG S B, et al. Characteristics of BeiDou navigation satellite system multipath and its mitigation method based on Kalman filter and rauch-tung-striebel smoother[J]. Sensors, 2018, 18 (1):198. DOI: 10.3390/s18010198.
    陶远, 邓永春, 胡豪杰, 等. 小波分析和经验模态分解对BDS多路径误差削弱对比研究[J]. 全球定位系统, 2019,44(3):49-55.
    NAJIBI N, JIN S G. Physical reflectivity and polarization characteristics for snow and icecovered surfaces interacting with gps signals[J]. [JP2]Remotesensing. 2013(5): 4006-4030.DOI: 10.3390/rs5084006.
    HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J]. Proceedings mathematical, physical andengineering sciences, 1998, 454(1971): 903-995.DOI: 10.1098/rspa.1998.0193.
    COLOMINAS M A, SCHLOTTHAUER G, TORRES M E. [JP]Improved complete ensemble EMD: a suitable tool for biomedical signal processing[J]. Biomedical signal processing and control, 2014(14): 19-29. DOI: 10.1016/j.bspc.2014.06.009.
    张敬霞. 层序地层格架下的煤系含气系统研究[D]. 徐州:中国矿业大学, 2018.
    HOCHREITER S, SCHMIDHUBER J. LSTM can solve hard long time lag problems[C]//Proceedings of the 9th international conference on neural information processing systems. 1997: 473-479. DOI: 10.5555/2998981.2999048.
    JIANG C H, CHEN Y W, CHEN S, et al. A mixed deep recurrent neural network for MEMS ggyroscope nnoise suuppressing[J]. Electronics, 2019, 8(2): 181. DOI: 10.3390/electronics8020181.
    SUNDERMEYER M, SCHLUTER R, NEY H. LSTM neural networks for language modeling[C]//Thirteenth Annual Conference of the International Speech Communication Association. 2012.DOI:10.1016/0165-6074(89)90269-x.
  • 期刊类型引用(5)

    1. 关志宇,钟秋文,韦晚秋,兰猗令,金相任. 基于CEEMDAN联合小波的GNSS边坡监测多路径误差处理研究. 现代信息科技. 2024(15): 60-64+68 . 百度学术
    2. 侯红科. 基于小波变换的单频伪距多路径误差研究. 城市勘测. 2023(02): 103-106 . 百度学术
    3. 徐精诚,连增增,董佳琪,岳哲. 基于小波包分解重构算法的北斗抗多路径误差. 科学技术与工程. 2022(35): 15477-15484 . 百度学术
    4. 罗正华,周方均,雷林,李霞,刘一达. 一种用于时差提取的卡尔曼-最优阶互相关算法. 科学技术与工程. 2021(12): 4982-4989 . 百度学术
    5. 彭学勤,董梦雪,马琳. 大数据背景下塑料光纤通信系统安全态势诊断研究. 塑料科技. 2020(08): 73-76 . 百度学术

    其他类型引用(3)

计量
  • 文章访问数:  509
  • HTML全文浏览量:  77
  • PDF下载量:  81
  • 被引次数: 8
出版历程
  • 刊出日期:  2020-04-14

目录

    /

    返回文章
    返回
    x 关闭 永久关闭