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Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement-A Review.

Shipeng Han1,2, Zhen Meng1, Olatunji Omisore3

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|November 25, 2020
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Summary
This summary is machine-generated.

This review examines random error processing models for microelectromechanical systems (MEMS) inertial sensors. It highlights methods to improve sensor accuracy and reliability by mitigating noise and artifacts.

Keywords:
MEMS accelerometerMEMS gyroscoperandom error reductionsignal processing algorithms

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Area of Science:

  • Engineering
  • Sensor Technology
  • Signal Processing

Background:

  • Microelectromechanical systems (MEMS) inertial sensors offer size, cost, and precision advantages for diverse applications.
  • MEMS accelerometers and gyroscopes are increasingly used in healthcare, defense, and other fields.
  • A key limitation is susceptibility to environmental noise, mechanical, and electronic artifacts, impacting accuracy.

Purpose of the Study:

  • To systematically review recent random error signal processing models for enhancing MEMS inertial sensor precision.
  • To analyze the contributions, strengths, and weaknesses of various algorithms.
  • To summarize developed models, their principles, applications, and findings.

Main Methods:

  • Conducted an in-depth literature search across major scientific databases (Web of Science, IEEE Xplore, Science Direct, ACM Digital Library).
  • Reviewed 49 representative papers published within the last 10 years focusing on MEMS accelerometers, gyroscopes, and inertial measurement units.
  • Extracted and categorized 30 mainstream algorithms into seven groups for analysis.

Main Results:

  • Identified and analyzed 30 mainstream algorithms for random error processing in MEMS inertial sensors.
  • Categorized algorithms based on their contributions, strengths, and weaknesses.
  • Summarized model principles, application domains, and study conclusions.

Conclusions:

  • Random error processing is crucial for improving MEMS inertial sensor accuracy and reliability.
  • The review provides a comprehensive overview of current signal processing techniques and their effectiveness.
  • Identified development trends and application prospects for MEMS inertial sensor technology.