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Improved virtual gyroscope technology based on "current" probability density model.

Jin-Long Song1, Zhi-Yong Shi1, Bin-Han Du1

  • 1Army Engineering University, Shijiazhuang 050003, China.

The Review of Scientific Instruments
|January 3, 2019
PubMed
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This study enhances virtual gyroscope technology for micro-electromechanical systems (MEMS) gyroscopes by introducing a "current" probability density model. This improves fusion accuracy during dynamic maneuvers, significantly reducing error compared to single gyroscope drift.

Area of Science:

  • Inertial Navigation Systems
  • Sensor Fusion
  • MEMS Technology

Background:

  • Micro-electromechanical systems (MEMS) gyroscopes suffer from low precision, particularly during dynamic maneuvers.
  • Traditional virtual gyroscope technology models maneuver angular acceleration as white noise, limiting fusion accuracy in dynamic states.

Purpose of the Study:

  • To improve the precision and accuracy of virtual gyroscope technology for MEMS gyroscopes.
  • To enhance data fusion accuracy during dynamic maneuvers by accurately modeling maneuvering angular rates.

Main Methods:

  • Introduced a "current" probability density model to accurately represent maneuvering angular rates.
  • Approximated one-step predictive angular acceleration to the mean value of current angular acceleration.

Related Experiment Videos

  • Modeled angular acceleration variance using the one-step predictive value, enabling adaptive adjustment of mean and variance.

    • Main Results:

    • The "current" probability density model significantly improved the modeling accuracy of maneuvering angular rates.
    • Enhanced virtual gyroscope technology demonstrated improved compensation accuracy.
    • Experimental results showed a 6.53 times lower 1σ standard deviation at low frequency and 2.04 times lower at high frequency compared to single gyroscope static drift.

    Conclusions:

    • The proposed "current" probability density model effectively improves virtual gyroscope fusion accuracy in dynamic conditions.
    • This adaptive approach enhances the reliability and performance of MEMS gyroscope systems.
    • The method offers a significant improvement over traditional techniques for dynamic maneuver compensation.