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High-Efficiency Wavelet Compressive Fusion for Improving MEMS Array Performance.

Siyuan Liang1, Weilong Zhu1, Feng Zhao1

  • 1Key Laboratory of Information Communication Network and Security, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.

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|March 21, 2020
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Summary
This summary is machine-generated.

This study introduces a wavelet compressive fusion (WCF) algorithm to enhance low-cost microelectromechanical systems (MEMS) inertial devices. The WCF algorithm improves accuracy and enables real-time processing for high-precision navigation applications.

Keywords:
MEMS arraycompressive fusioninertial navigation

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Area of Science:

  • Engineering
  • Signal Processing
  • Sensor Technology

Background:

  • Low-cost microelectromechanical systems (MEMS) inertial devices are widely used but limited by low precision and high noise.
  • High-precision applications require improved performance beyond current MEMS capabilities.

Purpose of the Study:

  • To propose a highly efficient optimal estimation algorithm for MEMS arrays to improve their performance.
  • To enhance the accuracy and enable real-time processing of MEMS inertial devices.

Main Methods:

  • Wavelet compressive fusion (WCF) algorithm utilizing multiscale wavelet transform for signal compression.
  • Fusing compressive data based on support and applying threshold processing to wavelet coefficients.

Main Results:

  • Simulation results show the algorithm performs well on inertial sensor array output.
  • Experimental results demonstrate a processing delay of approximately 75 ms for 100 ms of data, enabling real-time processing.
  • Zero-bias instability, angle random walk, and rate slope of gyroscopes improved by 8.0, 8.0, and 9.5 dB, respectively.

Conclusions:

  • The WCF algorithm offers outstanding real-time performance for MEMS array systems.
  • The proposed algorithm effectively improves the accuracy of low-cost MEMS inertial devices.