{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T13:58:12Z","timestamp":1721138292340},"reference-count":23,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2015,2,16]],"date-time":"2015-02-16T00:00:00Z","timestamp":1424044800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chinese University Science Foundation","award":["No. 2014QNJJ024"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Micromachines"],"abstract":"In this paper, a novel approach for processing the outputs signal of the microelectromechanical systems (MEMS) gyroscopes was presented to reduce the bias drift and noise. The principle for the noise reduction was presented, and an optimal Kalman filter (KF) was designed by a steady-state filter gain obtained from the analysis of KF observability. In particular, the true angular rate signal was directly modeled to obtain an optimal estimate and make a self-compensation for the gyroscope without needing other sensor\u2019s information, whether in static or dynamic condition. A linear fit equation that describes the relationship between the KF bandwidth and modeling parameter of true angular rate was derived from the analysis of KF frequency response. The test results indicated that the MEMS gyroscope having an ARW noise of 4.87\u00b0\/h0.5 and a bias instability of 44.41\u00b0\/h were reduced to 0.4\u00b0\/h0.5 and 4.13\u00b0\/h by the KF under a given bandwidth (10 Hz), respectively. The 1\u03c3 estimated error was reduced from 1.9\u00b0\/s to 0.14\u00b0\/s and 1.7\u00b0\/s to 0.5\u00b0\/s in the constant rate test and swing rate test, respectively. It also showed that the filtered angular rate signal could well reflect the dynamic characteristic of the input rate signal in dynamic conditions. The presented algorithm is proved to be effective at improving the measurement precision of the MEMS gyroscope. <\/jats:p>","DOI":"10.3390\/mi6020266","type":"journal-article","created":{"date-parts":[[2015,2,16]],"date-time":"2015-02-16T15:30:38Z","timestamp":1424100638000},"page":"266-280","source":"Crossref","is-referenced-by-count":20,"title":["Noise Reduction of MEMS Gyroscope Based on Direct Modeling for an Angular Rate Signal"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-0044-4598","authenticated-orcid":false,"given":"Liang","family":"Xue","sequence":"first","affiliation":[{"name":"Xi'an Research Inst. of Hi-Tech, Hongqing Town, Xi'an 710025, China"}]},{"given":"Chengyu","family":"Jiang","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Micro and Nano Systems for Aerospace, Northwestern Polytechnical University, 127 Youyi West Road, Xi'an 710072, China"}]},{"given":"Lixin","family":"Wang","sequence":"additional","affiliation":[{"name":"Xi'an Research Inst. of Hi-Tech, Hongqing Town, Xi'an 710025, China"}]},{"given":"Jieyu","family":"Liu","sequence":"additional","affiliation":[{"name":"Xi'an Research Inst. of Hi-Tech, Hongqing Town, Xi'an 710025, China"}]},{"given":"Weizheng","family":"Yuan","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Micro and Nano Systems for Aerospace, Northwestern Polytechnical University, 127 Youyi West Road, Xi'an 710072, China"}]}],"member":"1968","published-online":{"date-parts":[[2015,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1109\/JSEN.2003.815799","article-title":"Nonresonant micromachined gyroscopes with structural mode-decoupling","volume":"3","author":"Acar","year":"2003","journal-title":"IEEE Sens. 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