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MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array
Liang Xue1, Bo Yang1, Xinguo Wang1
1Department of Control Engineering, Xi'an Research Institute of High Technology, Hongqing Town, No. 2 Tongxin Road, Xi'an 710025, China.
Micromachines
|July 8, 2023
Summary
This study enhances micro-inertial measurement unit (MIMU) accuracy by using multiple MEMS gyroscopes in a non-orthogonal array with an optimal Kalman filter. This redundant system significantly reduces gyro noise and improves flight carrier motion sensing.
Area of Science:
- Aerospace Engineering
- Electrical Engineering
- Mechatronics
Background:
- Micro-inertial measurement units (MIMUs) are crucial for sensing angular rate and acceleration in flight carriers.
- Existing MIMU systems face limitations in accuracy due to inherent sensor noise and errors.
Purpose of the Study:
- To develop a redundant MIMU system using multiple MEMS gyroscopes in a spatial non-orthogonal array.
- To improve MIMU accuracy by combining array signals with an optimal Kalman filter (KF) algorithm.
- To analyze the impact of noise correlation and geometric layout on system performance.
Main Methods:
- Constructed a redundant MIMU system with multiple MEMS gyroscopes in a non-orthogonal array.
- Developed an optimal KF algorithm utilizing steady-state KF gain for signal fusion.
- Optimized array geometric layout based on noise correlation analysis.
- Designed and analyzed conical configurations for 4, 5, 6, and 8-gyro arrays.
- Verified the system with a redundant 4-MIMU configuration.
Main Results:
- The redundant MIMU system accurately estimates input signal rates.
- Gyroscope errors are effectively reduced through the fusion of non-orthogonal array signals.
- In a 4-MIMU system, Angle Random Walk (ARW) and Rate Random Walk (RRW) noise were reduced by approximately 3.5 and 2.5 times, respectively.
- Estimated errors on the X, Y, and Z axes were reduced by factors of 4.9, 4.6, and 2.9 compared to a single gyroscope.
Conclusions:
- A redundant MIMU system with a non-orthogonal gyroscope array and optimal KF significantly enhances accuracy.
- The proposed method effectively mitigates gyroscope noise (ARW and RRW) and reduces overall estimation errors.
- Optimizing array geometry and utilizing noise correlation are key to performance improvement in MIMU systems.
