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Improved Virtual Gyroscope Technology Based on the ARMA Model.

Jinlong Song1, Zhiyong Shi2, Lvhua Wang3

  • 1Department of Vehicle and Electrical Engineering, Army Engineering University, Shijiazhuang 050003, China. sjzsong_jl@163.com.

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|November 15, 2018
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Summary
This summary is machine-generated.

This study introduces an improved virtual gyroscope technology using the Autoregressive Moving Average (ARMA) model to enhance Micro-electro-mechanical Systems (MEMS) gyroscope precision. The ARMA-based approach significantly reduces output noise and improves accuracy compared to conventional methods.

Keywords:
MEMSautoregressive moving average (ARMA) modelrandom errorvirtual gyroscope

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Area of Science:

  • Engineering
  • Signal Processing
  • Instrumentation

Background:

  • Micro-electro-mechanical Systems (MEMS) gyroscopes suffer from high output noise and low precision.
  • Conventional virtual gyroscope technology has limitations in compensating for all random errors in MEMS gyroscopes.

Purpose of the Study:

  • To improve the output precision of MEMS gyroscopes by enhancing virtual gyroscope technology.
  • To address the limitations of conventional virtual gyroscope random error models.

Main Methods:

  • Implemented conventional virtual gyroscope technology with a Kalman filter for MEMS gyroscope data fusion.
  • Developed an improved virtual gyroscope technology incorporating an Autoregressive Moving Average (ARMA) model to refine the random error model.
  • Designed a Kalman filter based on the enhanced random error model for data fusion.

Main Results:

  • The improved virtual gyroscope technology based on the ARMA model demonstrated a 1.4 times lower 1σ standard deviation in output compared to the conventional method.
  • The ARMA model effectively improved the random error modeling for virtual gyroscope applications.

Conclusions:

  • The proposed ARMA-based virtual gyroscope technology offers a significant improvement in MEMS gyroscope precision.
  • This enhanced approach provides a more robust solution for compensating MEMS gyroscope errors in data fusion applications.