Improving the accuracy of a platformless inertial navigation system for an aircraft during rapid roll rotation

The article addresses the problem of enhancing the accuracy of an autonomous strapdown inertial navigation system (SINS) for aircraft with rapid rotation about their longitudinal axis. This rapid rotation stabilizes the aircraft's position along the longitudinal axis while imposing strict requirements on the roll gyroscope's scale factor (SF) error in the SINS. This is essential to ensure that the roll angle error remains on par with the pitch and yaw angle errors. A novel method for periodic correction of the roll gyroscope's SF within an autonomous SINS is proposed. The method utilizes signals from a single-axis indicator gyrostabilizer based on a microelectromechanical system (MEMS) gyroscope. The correction involves determining the numerical value of the roll gyroscope's SF error during flight and subsequently compensating for its influence on the roll angular velocity measurements. The functional scheme of the method is presented, along with formulas for calculating the correction coefficient. The efficiency of the proposed approach in improving the accuracy of the SINS is evaluated using a typical inertial module and an indicator gyrostabilizer with a MEMS gyroscope as an example. The method significantly enhances the accuracy of roll angular velocity and coordinate measurements in an autonomous SINS without requiring expensive precision gyroscopes.

Authors

Publication Details

Journal
MECHANICS OF GYROSCOPIC SYSTEMS
Published
2024-12-26
DOI
https://doi.org/10.20535/0203-3771482024317967
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving the accuracy of a platformless inertial navigation system for an aircraft during rapid roll rotation

Mykola Chernyak, E Hyzhnyak
MECHANICS OF GYROSCOPIC SYSTEMS
Inertial Sensor and Navigation
article

Improving the accuracy of a platformless inertial navigation system for an aircraft during rapid roll rotation

Mykola Chernyak, E Hyzhnyak
article en

Abstract

The article addresses the problem of enhancing the accuracy of an autonomous strapdown inertial navigation system (SINS) for aircraft with rapid rotation about their longitudinal axis. This rapid rotation stabilizes the aircraft's position along the longitudinal axis while imposing strict requirements on the roll gyroscope's scale factor (SF) error in the SINS. This is essential to ensure that the roll angle error remains on par with the pitch and yaw angle errors. A novel method for periodic correction of the roll gyroscope's SF within an autonomous SINS is proposed. The method utilizes signals from a single-axis indicator gyrostabilizer based on a microelectromechanical system (MEMS) gyroscope. The correction involves determining the numerical value of the roll gyroscope's SF error during flight and subsequently compensating for its influence on the roll angular velocity measurements. The functional scheme of the method is presented, along with formulas for calculating the correction coefficient. The efficiency of the proposed approach in improving the accuracy of the SINS is evaluated using a typical inertial module and an indicator gyrostabilizer with a MEMS gyroscope as an example. The method significantly enhances the accuracy of roll angular velocity and coordinate measurements in an autonomous SINS without requiring expensive precision gyroscopes.

MECHANICS OF GYROSCOPIC SYSTEMS(48)
Affordable and clean energy
Openalex Percentile: Top 59%
Inertial Sensor and Navigation
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.