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Related Experiment Video

Updated: Feb 10, 2026

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A Combined Gravity Compensation Method for INS Using the Simplified Gravity Model and Gravity Database.

Xiao Zhou1,2, Gongliu Yang3,4, Jing Wang5

  • 1School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China. by1317110@buaa.edu.cn.

Sensors (Basel, Switzerland)
|May 15, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new gravity compensation method to improve the accuracy of inertial navigation systems (INS). The combined approach enhances positioning accuracy by 20% and 38% in different terrains.

Keywords:
error modellingextreme learning machine (ELM)gravity compensationgravity modelhigh precision free-INS

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Area of Science:

  • Geodesy and Geophysics
  • Navigation Systems Engineering

Background:

  • High-precision inertial navigation systems (INS) are susceptible to position errors caused by gravity.
  • Accurate gravity compensation is crucial for enhancing INS performance, particularly with advanced inertial sensors.

Purpose of the Study:

  • To develop and validate a novel combined gravity compensation method for INS.
  • To improve the navigation accuracy of INS by addressing gravity disturbances.

Main Methods:

  • Deduction of INS solution error considering gravity disturbance.
  • A two-step gravity compensation: subtracting normal gravity via a simplified model and compensating gravity disturbance using ELM-trained gravity database.
  • Verification through vehicle tests in diverse terrains.

Main Results:

  • The proposed method effectively reduces INS position error.
  • Positioning accuracy improved by 20% in flat terrain and 38% in complex terrain during 2-hour tests.
  • Demonstrated feasibility and effectiveness across varying geographical conditions.

Conclusions:

  • The combined gravity compensation method significantly enhances INS positioning accuracy.
  • This approach offers a practical solution for improving INS performance in real-world applications.
  • The method is validated for both mild and severe gravity variation environments.