{"title":"Combining numerous gyroscopes for accuracy improvement using autoregressive process for rate signal modeling","authors":"Qiang Shen, Jieyu Liu, W. Qin, Huang Huang","doi":"10.1109/CGNCC.2016.7828892","DOIUrl":null,"url":null,"abstract":"A signal processing technique for gyro array is presented in this paper to reduce noise and improve the accuracy of micro-electro-mechanical system (MEMS) gyroscope. To improve the dynamic performance, the true rate is modeled by an autoregressive (AR) model instead of a random walk. According to the analysis results of the Allan variance, the measurement model is simplified and a mathematical model is established. Based on this model, a novel Kalman filter (KF) with modified estimation process for combining outputs of a gyroscope array is designed. The performance and the affect factors of the gyro array are analyzed by using a steady-state covariance. The experimental results indicate that the RMSE of the gyroscopes can be reduced from 0.4925 deg/s to 0.0034 deg/s by an array composed of six gyroscopes in static test. The dynamic test is also discussed and the validity of the proposed modeling and fusion method is proved.","PeriodicalId":426650,"journal":{"name":"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGNCC.2016.7828892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A signal processing technique for gyro array is presented in this paper to reduce noise and improve the accuracy of micro-electro-mechanical system (MEMS) gyroscope. To improve the dynamic performance, the true rate is modeled by an autoregressive (AR) model instead of a random walk. According to the analysis results of the Allan variance, the measurement model is simplified and a mathematical model is established. Based on this model, a novel Kalman filter (KF) with modified estimation process for combining outputs of a gyroscope array is designed. The performance and the affect factors of the gyro array are analyzed by using a steady-state covariance. The experimental results indicate that the RMSE of the gyroscopes can be reduced from 0.4925 deg/s to 0.0034 deg/s by an array composed of six gyroscopes in static test. The dynamic test is also discussed and the validity of the proposed modeling and fusion method is proved.