Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A Review
Research and industrial studies have indicated that small size, low cost, high precision, and ease of integration are vital features that characterize microelectromechanical systems (MEMS) inertial sensors for mass production and diverse applications. In recent times, sensors like MEMS accelerometer...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/11/11/1021 |
| _version_ | 1797547190910976000 |
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| author | Shipeng Han Zhen Meng Olatunji Omisore Toluwanimi Akinyemi Yuepeng Yan |
| author_facet | Shipeng Han Zhen Meng Olatunji Omisore Toluwanimi Akinyemi Yuepeng Yan |
| author_sort | Shipeng Han |
| collection | DOAJ |
| description | Research and industrial studies have indicated that small size, low cost, high precision, and ease of integration are vital features that characterize microelectromechanical systems (MEMS) inertial sensors for mass production and diverse applications. In recent times, sensors like MEMS accelerometers and MEMS gyroscopes have been sought in an increased application range such as medical devices for health care to defense and military weapons. An important limitation of MEMS inertial sensors is repeatedly documented as the ease of being influenced by environmental noise from random sources, along with mechanical and electronic artifacts in the underlying systems, and other random noise. Thus, random error processing is essential for proper elimination of artifact signals and improvement of the accuracy and reliability from such sensors. In this paper, a systematic review is carried out by investigating different random error signal processing models that have been recently developed for MEMS inertial sensor precision improvement. For this purpose, an in-depth literature search was performed on several databases viz., Web of Science, IEEE Xplore, Science Direct, and Association for Computing Machinery Digital Library. Forty-nine representative papers that focused on the processing of signals from MEMS accelerometers, MEMS gyroscopes, and MEMS inertial measuring units, published in journal or conference formats, and indexed on the databases within the last 10 years, were downloaded and carefully reviewed. From this literature overview, 30 mainstream algorithms were extracted and categorized into seven groups, which were analyzed to present the contributions, strengths, and weaknesses of the literature. Additionally, a summary of the models developed in the studies was presented, along with their working principles viz., application domain, and the conclusions made in the studies. Finally, the development trend of MEMS inertial sensor technology and its application prospects were presented. |
| first_indexed | 2024-03-10T14:39:45Z |
| format | Article |
| id | doaj.art-39ec61fc47404d22ad4e62dcd9f2fb58 |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-03-10T14:39:45Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-39ec61fc47404d22ad4e62dcd9f2fb582023-11-20T21:50:39ZengMDPI AGMicromachines2072-666X2020-11-011111102110.3390/mi11111021Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A ReviewShipeng Han0Zhen Meng1Olatunji Omisore2Toluwanimi Akinyemi3Yuepeng Yan4Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, ChinaInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, ChinaShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, ChinaResearch and industrial studies have indicated that small size, low cost, high precision, and ease of integration are vital features that characterize microelectromechanical systems (MEMS) inertial sensors for mass production and diverse applications. In recent times, sensors like MEMS accelerometers and MEMS gyroscopes have been sought in an increased application range such as medical devices for health care to defense and military weapons. An important limitation of MEMS inertial sensors is repeatedly documented as the ease of being influenced by environmental noise from random sources, along with mechanical and electronic artifacts in the underlying systems, and other random noise. Thus, random error processing is essential for proper elimination of artifact signals and improvement of the accuracy and reliability from such sensors. In this paper, a systematic review is carried out by investigating different random error signal processing models that have been recently developed for MEMS inertial sensor precision improvement. For this purpose, an in-depth literature search was performed on several databases viz., Web of Science, IEEE Xplore, Science Direct, and Association for Computing Machinery Digital Library. Forty-nine representative papers that focused on the processing of signals from MEMS accelerometers, MEMS gyroscopes, and MEMS inertial measuring units, published in journal or conference formats, and indexed on the databases within the last 10 years, were downloaded and carefully reviewed. From this literature overview, 30 mainstream algorithms were extracted and categorized into seven groups, which were analyzed to present the contributions, strengths, and weaknesses of the literature. Additionally, a summary of the models developed in the studies was presented, along with their working principles viz., application domain, and the conclusions made in the studies. Finally, the development trend of MEMS inertial sensor technology and its application prospects were presented.https://www.mdpi.com/2072-666X/11/11/1021MEMS gyroscopeMEMS accelerometerrandom error reductionsignal processing algorithms |
| spellingShingle | Shipeng Han Zhen Meng Olatunji Omisore Toluwanimi Akinyemi Yuepeng Yan Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A Review Micromachines MEMS gyroscope MEMS accelerometer random error reduction signal processing algorithms |
| title | Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A Review |
| title_full | Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A Review |
| title_fullStr | Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A Review |
| title_full_unstemmed | Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A Review |
| title_short | Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement—A Review |
| title_sort | random error reduction algorithms for mems inertial sensor accuracy improvement a review |
| topic | MEMS gyroscope MEMS accelerometer random error reduction signal processing algorithms |
| url | https://www.mdpi.com/2072-666X/11/11/1021 |
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