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International Journal of Sensors, Wireless Communications and Control

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ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

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Research Article

Wavelet DE-noising and Kalman Filtering of MEMS Sensors for Autonomous Latitude Determination

Author(s): Vadym Avrutov*, Nadiia Bouraou, Sergii Davydenko, Oleksii Hehelskyi, Sergii Lakoza, Olena Matvienko and Olha Pazdrii

Volume 12, Issue 5, 2022

Published on: 07 July, 2022

Page: [344 - 351] Pages: 8

DOI: 10.2174/2210327912666220511232427

Price: $65

Abstract

Background: There is a task of autonomous determination of the position latitude of unmoved vehicles. Also, there is another task of the initial value latitude determination as a prepared operation of gimbaled and strap-down inertial navigation systems. For both cases, it is necessary to have an inertial measurement unit (IMU) with triad gyroscopes and triad accelerometers. The output signals of micromechanical gyroscopes and accelerometers have large noise components when using the IMU in the micromachined electromechanical systems (MEMS) technology.

Objective: Normally to filter output signals of MEMS sensors, averaging and filtering are used. However, for Kalman filtering, it is necessary to find the exact mathematical model of the sensors and a lot of their initial random characteristics. The study of the possibility of the wavelet transform usage to filter the output signals MEMS accelerometers and gyroscopes for the latitude autonomous determination was conducted in the paper.

Methods: The wavelet transform approach was used to filter the output signals of MEMS accelerometers and gyroscopes in order to improve the accuracy of the autonomous position latitude determination. The autonomous latitude determination efficiency of IMU based on MEMS gyroscopes and accelerometers has been experimentally confirmed. The projections of the Earth’s angular rate and gravitational acceleration were obtained from the MEMS IMU. After that, the signals of the IMU gyroscopes and accelerometers were filtered, using the wavelet ‘Daubechies’ in decomposition, and averaged. These signals were used in a computational algorithm to determine the latitude.

Results: The results showed that Unlike the well-known Kalman filter wavelet de-noising reduced calculation error by almost twice.

Conclusion: Wavelet de-noising could be used for output signals filtering of micromechanical gyroscopes and accelerometers for the autonomous determination of position latitude.

Keywords: Gyroscopes, accelerometers, latitude determination, wavelets, inertial measurement unit, MEMS, IMU.

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