Design and analysis of a novel virtual gyroscope with multi-gyroscope and accelerometer array.

Area of Science:

• Inertial Navigation Systems
• Sensor Fusion
• Robotics

Background:

• Accurate angular rate measurement is crucial for navigation and control systems.
• Traditional gyroscopes face limitations in performance and error characteristics.
• Multi-sensor arrays offer potential for improved accuracy through data fusion.

Purpose of the Study:

• To propose a novel virtual gyroscope system utilizing a multi-gyroscope and accelerometer array (MGAA).
• To enhance the performance of angular rate measurement by fusing gyroscope and accelerometer data.
• To validate the proposed virtual gyroscope's effectiveness through static and dynamic testing.

Main Methods:

• Development of a virtual gyroscope integrating multiple gyroscopes and accelerometers.
• Implementation of a novel Kalman filter for signal merging, incorporating MEMS gyroscope error models and rigid body kinematics.
• Experimental verification using a typical MGAA configuration with four accelerometers and three gyroscopes.

Main Results:

• Static performance metrics showed significant improvements: angular random walk (ARW) reduced from 0.019°/√s to 0.0074°/√s, and bias instability decreased from 14.4°/h to 8.7°/h.
• Dynamic test results demonstrated a reduction in average root mean square error (RMSE) from 0.274°/s to 0.133°/s.
• The virtual gyroscope achieved approximately 44.1% and 44.5% higher improvement factors for ARW and RMSE, respectively, compared to published multi-gyroscope array methods.

Conclusions:

• The proposed virtual gyroscope with MGAA effectively improves angular rate measurement accuracy.
• The novel Kalman filter approach successfully fuses sensor data, mitigating gyroscope errors.
• This system offers superior static and dynamic performance, presenting a promising advancement for inertial sensing applications.