2010•Applied Mechanics and MaterialsOpen access

MEMS Gyroscope Random Error Modeling and Filtering

Bo Ren, De Ming Zhang, Huan Li

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Abstract

MEMS gyroscope is a new type of inertial device with small size, low cost, light weight, high reliability, but less precise and random error is relatively large. In this paper, from a practical engineering application point of view, first, the MEMS gyroscope random errors is real-time average filtered. Then, based on the basic principle of time series analysis of random sequence , the first-order AR model of MEMS gyroscope random errors is established. Finally, based on Markov characteristic of kalman filtering algorithm, each output of the MEMS gyroscope is multiple real-time filtered. Through the specific data processing, MEMS gyroscope random errors reduced to about two per cent of the original.

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What this paper is about

MEMS gyroscope is a new type of inertial device with small size, low cost, light weight, high reliability, but less precise and random error is relatively large. In this paper, from a practical engineering application point of view, first, the MEMS gyroscope random errors is real-time average filtered. Then, based on the basic principle of time series analysis of random sequence , the first-order AR model of MEMS gyroscope random errors is established. Finally, based on Markov characteristic of kalman filtering algorithm, each output of the MEMS gyroscope is multiple real-time filtered. Through the specific data processing, MEMS gyroscope random errors reduced to about two per cent of the original.

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Available abstract

MEMS gyroscope is a new type of inertial device with small size, low cost, light weight, high reliability, but less precise and random error is relatively large. In this paper, from a practical engineering application point of view, first, the MEMS gyroscope random errors is real-time average filtered. Then, based on the basic principle of time series analysis of random sequence , the first-order AR model of MEMS gyroscope random errors is established. Finally, based on Markov characteristic of kalman filtering algorithm, each output of the MEMS gyroscope is multiple real-time filtered. Through the specific data processing, MEMS gyroscope random errors reduced to about two per cent of the original.

Key concepts: Gyroscope, Vibrating structure gyroscope, Kalman filter, Rate integrating gyroscope, Microelectromechanical systems, Inertial measurement unit, Control theory (sociology), Algorithm

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