Robust M-estimation filter for MEMS gyro array processing

Kuan Ying Huang, Jyh Ching Juang, Tom Lin, Ming Yu Hsieh

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

Due to the rapid development in semiconductor technology, MEMS (microelectromechanical system)-based sensors have been widely used in commercial and military applications. These sensors are characterized by their small size, low cost, low power consumption. However, MEMS sensors are noted for their low accuracy, limiting the applicability in high precision navigation and control. In this paper, a MEMS gyroscope array is developed to account for the limitation of an individual sensor. The key is to develop a robust M-estimation filter to process the sensor array data in real time so as to provide a more accurate estimate of the angular rate, to render fault tolerance capability, and to facilitate signal quality index for system integration. The robust M-estimation Kalman filter is implemented in a DSP/FPGA platform to account for random bias and random walk. In addition, the M-estimation technique is used to accommodate outliers. Allan variance and FFT method are employed as an analyzing tool to quantify the performance. It is verified that the proposed robust M-estimation filter is capable of suppressing non-Gaussian impulse noise and providing a high-Accuracy angular rate measurement.

原文English
主出版物標題2016 International Automatic Control Conference, CACS 2016
發行者Institute of Electrical and Electronics Engineers Inc.
頁面179-184
頁數6
ISBN(電子)9781509041084
DOIs
出版狀態Published - 2017 七月 10
事件2016 International Automatic Control Conference, CACS 2016 - Taichung, Taiwan
持續時間: 2016 十一月 92016 十一月 11

出版系列

名字2016 International Automatic Control Conference, CACS 2016

Other

Other2016 International Automatic Control Conference, CACS 2016
國家Taiwan
城市Taichung
期間16-11-0916-11-11

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering
  • Control and Optimization

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