Optimal Compensation of MEMS Gyroscope Noise Kalman Filter Based on Conv-DAE and MultiTCN-Attention Model in Static Base Environment

Optimal Compensation of MEMS Gyroscope Noise Kalman Filter Based on Conv-DAE and MultiTCN-Attention Model in Static Base Environment

Errors in microelectromechanical systems (MEMS) inertial measurement units (IMUs) are large, complex, nonlinear, and time varying. The traditional noise reduction and compensation methods based on traditional models are not applicable. This paper proposes a noise reduction method based on multi-laye...

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Bibliographic Details
Main Authors: Zimin Huo, Fuchao Wang, Honghai Shen, Xin Sun, Jingzhong Zhang, Yaobin Li, Hairong Chu
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Sensors
Subjects:
MEMS gyroscope
convolutional denoising autoencoder
temporal convolutional network
attention mechanism
Particle Swarm Optimization algorithm
Kalman filter
Online Access:https://www.mdpi.com/1424-8220/22/19/7249

Internet

https://www.mdpi.com/1424-8220/22/19/7249

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