Research on the Error of Global Positioning System Based on Time Series Analysis.

Lijun Song, Lei Zhou, Peiyu Xu, Wanliang Zhao, Shaoliang Li, Zhe Li
Author Information
  1. Lijun Song: School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China. ORCID
  2. Lei Zhou: School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China. ORCID
  3. Peiyu Xu: School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
  4. Wanliang Zhao: Shanghai Aerospace Control Technology Institute, Shanghai 201100, China.
  5. Shaoliang Li: Shanghai Aerospace Control Technology Institute, Shanghai 201100, China.
  6. Zhe Li: School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.

Abstract

Due to the poor dynamic positioning precision of the Global Positioning System (GPS), Time Series Analysis (TSA) and Kalman filter technology are used to construct the positioning error of GPS. According to the statistical characteristics of the autocorrelation function and partial autocorrelation function of sample data, the Autoregressive (AR) model which is based on a Kalman filter is determined, and the error model of GPS is combined with a Kalman filter to eliminate the random error in GPS dynamic positioning data. The least square method is used for model parameter estimation and adaptability tests, and the experimental results show that the absolute value of the maximum error of longitude and latitude, the mean square error of longitude and latitude and average absolute error of longitude and latitude are all reduced, and the dynamic positioning precision after correction has been significantly improved.

Keywords

References

  1. Sensors (Basel). 2020 Nov 18;20(22): [PMID: 33218107]
  2. Sensors (Basel). 2020 Dec 13;20(24): [PMID: 33322229]

Grants

  1. 2020JM-488/Natural Science Foundation of Shaanxi Province
  2. 20JK0728/special scientific research project of the Education Department of Shaanxi Province

MeSH Term

Geographic Information Systems
Research Design
Time Factors

Word Cloud

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