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A Method for Oscillation Errors Restriction of SINS Based on Forecasted Time Series
Lin Zhao1, Jiushun Li2, Jianhua Cheng3
1College of Automation, Harbin Engineering University, Harbin 150001, China. zhaolin@hrbeu.edu.cn.
Sensors (Basel, Switzerland)
|July 21, 2015
Summary
This study introduces a novel method to improve the real-time accuracy of strapdown inertial navigation systems (SINS). By forecasting time series data from inertial measurement units (IMUs), it effectively restricts periodic oscillation errors.
Area of Science:
- Navigation Systems
- Inertial Navigation
- Signal Processing
Background:
- Strapdown inertial navigation systems (SINS) performance relies on continuity, real-time accuracy, and precision.
- Schuler, Foucault, and Earth's periodic oscillations degrade SINS real-time accuracy.
Purpose of the Study:
- To propose a novel method for restricting periodic oscillation errors in SINS.
- To enhance the real-time accuracy of SINS by addressing specific error sources.
Main Methods:
- Utilizing forecasted time series data from inertial measurement unit (IMU) measurements.
- Applying curve-fitting with the least squares method to obtain forecasted time series.
- Distinguishing and removing small angular motion interference during initial alignment.
- Implementing a half-wave delay mean value method to eliminate periodic oscillation signals.
Main Results:
- Successfully gained multiple navigation solutions with varying phase delays.
- Demonstrated effective restriction of Schuler, Foucault, and Earth periodic oscillation errors.
- Validated the method's performance through simulations and practical tests.
Conclusions:
- The proposed method significantly improves SINS real-time accuracy.
- Forecasting time series data is a viable strategy for mitigating SINS oscillation errors.
- The technique offers a robust solution for enhancing navigation system performance.
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