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Attitude Algorithm of Gyroscope-Free Strapdown Inertial Navigation System Using Kalman Filter.
Xiong Jiang1, Tao Liu1, Jie Duan1
1School of Opto-Electronic Engineering, Changchun University of Science and Technology, Changchun 130022, China.
Micromachines
|March 28, 2024
Summary
This study introduces a novel gyroscope-free strapdown inertial navigation system (GFSINS) using accelerometers for precise attitude determination. The new Kalman filter-based algorithm significantly improves angular velocity calculation accuracy for navigation systems.
Area of Science:
- Inertial Navigation Systems
- Sensor Fusion
- Attitude Determination
Background:
- Traditional inertial navigation systems often rely on gyroscopes, which can be bulky and expensive.
- Gyroscope-free strapdown inertial navigation systems (GFSINS) offer a potential alternative by utilizing accelerometers for attitude calculation.
- Accurate angular velocity calculation is critical for GFSINS performance, but existing methods face challenges like sign misjudgment.
Purpose of the Study:
- To propose and validate a novel angular velocity fusion algorithm for a twelve-accelerometer GFSINS.
- To enhance the accuracy of angular velocity calculation by addressing sign misjudgment issues.
- To achieve high-precision attitude determination for applications like laser scanning projection systems.
Main Methods:
- Analysis of a twelve-accelerometer configuration for GFSINS.
- Development of a Kalman filter-based algorithm for angular velocity fusion.
- Implementation of a sliding window correction method to improve extraction algorithm accuracy.
- Fusion of integral and improved extraction algorithm data for optimal angular velocity estimation.
Main Results:
- The proposed algorithm significantly reduces angular velocity error (maximum value and standard deviation) by one order of magnitude compared to existing methods.
- Experimental results show calculated attitude angles with an average difference of less than 0.5° compared to laser tracker measurements.
- The achieved accuracy meets the stringent requirements for attitude measurement in laser scanning projection systems.
Conclusions:
- The developed Kalman filter-based fusion algorithm effectively enhances angular velocity calculation accuracy in GFSINS.
- The sliding window correction method successfully mitigates sign misjudgment issues.
- This GFSINS approach provides a viable, high-accuracy solution for attitude determination in demanding applications.
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