The Influence of Atmospheric Density Error on SINS/RCNS Integrated Navigation

The atmospheric density error affects the accuracy of the Strap-down inertial navigation system (SINS)/Refraction celestial navigation system (RCNS) integrated navigation seriously by degrading the accuracy of the atmospheric refraction model. At present, the mechanism and extent of the impacts of atmospheric density error on measurements measurement models of SINS/RCNS integrated navigation are unclear. To solve this problem, this study first derives the relationship among atmospheric density error, measurements and measurement models (including refraction apparent height, refraction angle, and star pixel coordinates) of SINS/RCNS integrated navigation. Then, the quantitative relationship is provided based on it. The results show that 3.0% atmospheric density error can cause errors of 190.22 m in refraction apparent height measurement, 4.40" in refraction angle measurement model, and 0.13 pixels in star pixel coordinates measurement model. And these errors increase approximately linearly with the increase of atmospheric density error. Furthermore, simulations are carried out to verified the theoretical derivation and the linear relationship between the impacts of the atmospheric density error, which has a significant impact on position error and a relatively small impact on velocity error and posture error. When the atmospheric density error are 3.0%, 6.0%, and 9.0%, the position errors of the SINS/RCNS integrated navigation are about 1.4 times, 2.1 times, and 2.9 times of those without atmospheric density error. The research provides a theoretical basis for the elimination of the atmospheric density error.

Authors

Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-05-27
DOI
https://doi.org/10.1109/jiot.2025.3574026
Citations
2
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
9.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Influence of Atmospheric Density Error on SINS/RCNS Integrated Navigation

Yang Gao, Xiaolin Ning, Yuqing Yang, Jinhu Lü et al.
2 citations
IEEE Internet of Things Journal
Inertial Sensor and Navigation
9.99
article

The Influence of Atmospheric Density Error on SINS/RCNS Integrated Navigation

Yang Gao, Xiaolin Ning, Yuqing Yang, Jinhu Lü, Huang Yueqing, Yang Haonan, Ou Xinya
article en
2 citations

Abstract

The atmospheric density error affects the accuracy of the Strap-down inertial navigation system (SINS)/Refraction celestial navigation system (RCNS) integrated navigation seriously by degrading the accuracy of the atmospheric refraction model. At present, the mechanism and extent of the impacts of atmospheric density error on measurements measurement models of SINS/RCNS integrated navigation are unclear. To solve this problem, this study first derives the relationship among atmospheric density error, measurements and measurement models (including refraction apparent height, refraction angle, and star pixel coordinates) of SINS/RCNS integrated navigation. Then, the quantitative relationship is provided based on it. The results show that 3.0% atmospheric density error can cause errors of 190.22 m in refraction apparent height measurement, 4.40" in refraction angle measurement model, and 0.13 pixels in star pixel coordinates measurement model. And these errors increase approximately linearly with the increase of atmospheric density error. Furthermore, simulations are carried out to verified the theoretical derivation and the linear relationship between the impacts of the atmospheric density error, which has a significant impact on position error and a relatively small impact on velocity error and posture error. When the atmospheric density error are 3.0%, 6.0%, and 9.0%, the position errors of the SINS/RCNS integrated navigation are about 1.4 times, 2.1 times, and 2.9 times of those without atmospheric density error. The research provides a theoretical basis for the elimination of the atmospheric density error.

IEEE Internet of Things JournalVol. 12(15)
Inner Mongolia University (CN), Beihang University (CN)
Climate action
Openalex Percentile: Top 3%
Inertial Sensor and Navigation
9.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.