军用微机电系统陀螺仪灵敏度的改进

Abhinav G A, Anita Shirur, Divya Kannur, Harshit Bagewadi, Chandrashekhar Vaidyanathan
{"title":"军用微机电系统陀螺仪灵敏度的改进","authors":"Abhinav G A, Anita Shirur, Divya Kannur, Harshit Bagewadi, Chandrashekhar Vaidyanathan","doi":"10.1109/SPIN48934.2020.9070932","DOIUrl":null,"url":null,"abstract":"In this paper, we have devised a novel approach for processing the output signal of the micro electro-mechanical systems (MEMS) gyroscopes for the reduction of noise. The main principles on which the model is developed are Allan Variance and Kalman Filtering. The true angular rate signal in all the three directions were directly modeled to obtain an optimal estimate and to develop a self-compensation for the system without the need of any other sensor information, whether in static or dynamic condition. The Allan variance equation was implemented in order to obtain the noise reactivity of gyroscope and to model the noise components. Then, an optimal Kalman filter model was designed and developed to filter-out the noise and provide an ideal or a likely ideal output, which is noise free. A filtering model for a three-dimensional gyroscope is designed, developed and implemented.","PeriodicalId":126759,"journal":{"name":"2020 7th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Improvements in The Sensitivity Of Mems Based Gyroscope For Military Applications\",\"authors\":\"Abhinav G A, Anita Shirur, Divya Kannur, Harshit Bagewadi, Chandrashekhar Vaidyanathan\",\"doi\":\"10.1109/SPIN48934.2020.9070932\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we have devised a novel approach for processing the output signal of the micro electro-mechanical systems (MEMS) gyroscopes for the reduction of noise. The main principles on which the model is developed are Allan Variance and Kalman Filtering. The true angular rate signal in all the three directions were directly modeled to obtain an optimal estimate and to develop a self-compensation for the system without the need of any other sensor information, whether in static or dynamic condition. The Allan variance equation was implemented in order to obtain the noise reactivity of gyroscope and to model the noise components. Then, an optimal Kalman filter model was designed and developed to filter-out the noise and provide an ideal or a likely ideal output, which is noise free. A filtering model for a three-dimensional gyroscope is designed, developed and implemented.\",\"PeriodicalId\":126759,\"journal\":{\"name\":\"2020 7th International Conference on Signal Processing and Integrated Networks (SPIN)\",\"volume\":\"108 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 7th International Conference on Signal Processing and Integrated Networks (SPIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPIN48934.2020.9070932\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 7th International Conference on Signal Processing and Integrated Networks (SPIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIN48934.2020.9070932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

在本文中,我们设计了一种新的方法来处理微机电系统(MEMS)陀螺仪的输出信号,以降低噪声。建立模型的主要原理是Allan方差和卡尔曼滤波。在静态或动态情况下,直接对三个方向的真实角速度信号进行建模,以获得最优估计并开发系统的自补偿,而无需任何其他传感器信息。为了得到陀螺仪的噪声反应性并对噪声分量进行建模,采用了Allan方差方程。然后,设计并开发了一种最优卡尔曼滤波模型,以滤除噪声并提供无噪声的理想或似理想输出。设计、开发并实现了三维陀螺仪的滤波模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improvements in The Sensitivity Of Mems Based Gyroscope For Military Applications
In this paper, we have devised a novel approach for processing the output signal of the micro electro-mechanical systems (MEMS) gyroscopes for the reduction of noise. The main principles on which the model is developed are Allan Variance and Kalman Filtering. The true angular rate signal in all the three directions were directly modeled to obtain an optimal estimate and to develop a self-compensation for the system without the need of any other sensor information, whether in static or dynamic condition. The Allan variance equation was implemented in order to obtain the noise reactivity of gyroscope and to model the noise components. Then, an optimal Kalman filter model was designed and developed to filter-out the noise and provide an ideal or a likely ideal output, which is noise free. A filtering model for a three-dimensional gyroscope is designed, developed and implemented.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信