Adaptive filtering for MEMS gyroscope with dynamic noise model

Yuting Bai; Xiaoyi Wang; Xuebo Jin; Tingli Su; Jianlei Kong; Baihai Zhang

doi:10.1016/j.isatra.2020.01.030

Adaptive filtering for MEMS gyroscope with dynamic noise model

ISA Trans. 2020 Jun:101:430-441. doi: 10.1016/j.isatra.2020.01.030. Epub 2020 Feb 1.

Authors

Yuting Bai¹, Xiaoyi Wang², Xuebo Jin³, Tingli Su⁴, Jianlei Kong⁵, Baihai Zhang⁶

Affiliations

¹ School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China; China Light Industry Key Laboratory of Industrial Internet and Big Data, Beijing Technology and Business University, Beijing, 100048, China. Electronic address: baiyuting@btbu.edu.cn.
² School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China; China Light Industry Key Laboratory of Industrial Internet and Big Data, Beijing Technology and Business University, Beijing, 100048, China. Electronic address: wangxy@btbu.edu.cn.
³ School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China; China Light Industry Key Laboratory of Industrial Internet and Big Data, Beijing Technology and Business University, Beijing, 100048, China. Electronic address: jinxuebo@btbu.edu.cn.
⁴ School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China; China Light Industry Key Laboratory of Industrial Internet and Big Data, Beijing Technology and Business University, Beijing, 100048, China. Electronic address: sutingli@btbu.edu.cn.
⁵ School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China; China Light Industry Key Laboratory of Industrial Internet and Big Data, Beijing Technology and Business University, Beijing, 100048, China. Electronic address: kongjianlei@btbu.edu.cn.
⁶ School of Automation, Beijing Institute of Technology, Beijing, 100081, China. Electronic address: smczhang@bit.edu.cn.

PMID: 32033797
DOI: 10.1016/j.isatra.2020.01.030

Abstract

MEMS (Micro-Electro-Mechanical Systems) gyroscope is the core component in the posture recognition and assistant positioning, of which the complex noise limits its performance. It is essential to filter the noise and obtain the true value of the measurements. Then an adaptive filtering method was proposed. Firstly, noises of MEMS gyroscope were analyzed to build the basic framework of the dynamic noise model. Secondly, the dynamic Allan variance was improved with a novel truncation window based on the entropy features, which referred to the parameters in the noise model. Thirdly, the adaptive Kalman filter was derived from the dynamic noise model. Finally, the simulation and experiment were carried out to verify the method. The results prove that the improved dynamic Allan variance can extract noise feature distinctly, and the filtering precision in the new method is relatively high.

Keywords: Adaptive filtering; Dynamic Allan variance; Kalman filter; MEMS gyroscope.