Research on GNSS Positioning Aided by SVR

  • Zhifei YangEmail author
  • Tianfeng Yan
  • Yifei Yang
  • Jinping Qi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 905)


In order to solve the problem of the influence of the surrounding environment on GNSS signal leads to the loss of GNSS measurement. Introducing the least squares support vector regression LS-SVR and the monotonicity of geological short-term subsidence deformation, the model of LS-SVR assisted GNSS positioning is established. To explain the model, a GNSS settlement monitoring experiment was adopted. Example analysis shows when GNSS monitoring points are seriously affected by the surrounding area, the LS-GNSS model can obtain more stable positioning results. It eliminates the serious positioning error under the GNSS unlock, achieves the positioning ability under the ideal environment, expands the use range of the GNSS positioning, and improves the positioning accuracy of the GNSS.


Measurement Monitor SVR GNSS 



This study is supported by Gansu science and Technology Department (17YF1FA122); Lanzhou Science and Technology Bureau (2018-1-51); School youth fund of Lanzhou Jiaotong University (2015008).


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Zhifei Yang
    • 1
    Email author
  • Tianfeng Yan
    • 1
  • Yifei Yang
    • 2
  • Jinping Qi
    • 1
  1. 1.School of Electronic and Information EngineeringLanzhou Jiaotong UniversityLanzhouChina
  2. 2.Taiyuan Works SectionDaqin Railway Co., Ltd.TaiyuanChina

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