基于低成本MEMS传感器阵列的纯惯性导航

Lukas Blocher, Wolfram Mayer, M. Arena, Dusan Radovic, T. Hiller, J. Gerlach, O. Bringmann
{"title":"基于低成本MEMS传感器阵列的纯惯性导航","authors":"Lukas Blocher, Wolfram Mayer, M. Arena, Dusan Radovic, T. Hiller, J. Gerlach, O. Bringmann","doi":"10.1109/INERTIAL51137.2021.9430468","DOIUrl":null,"url":null,"abstract":"This paper examines the position precision of purely inertial navigation using an array of redundant, low-cost MEMS sensors. A carefully designed IMU is used to perform navigation experiments and to analyze the benefits of a sensor array over a single sensor in practice. As our experimental results show, navigation can be improved significantly by calibrating the IMU device regarding scale factors, offsets and cross-axis sensitivity. By comparing predicted navigation error and experimental results it is shown that gyroscope angle random walk and bias instability are dominant and therefore can be used to estimate naviaation performance. The latter improves roughly by a factor of $\\sqrt{14}$ when using an array of 14 devices instead of a single one. A Kalman Filter with motion constraints minimizes the error when estimating positions.","PeriodicalId":424028,"journal":{"name":"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Purely Inertial Navigation with a Low-Cost MEMS Sensor Array\",\"authors\":\"Lukas Blocher, Wolfram Mayer, M. Arena, Dusan Radovic, T. Hiller, J. Gerlach, O. Bringmann\",\"doi\":\"10.1109/INERTIAL51137.2021.9430468\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper examines the position precision of purely inertial navigation using an array of redundant, low-cost MEMS sensors. A carefully designed IMU is used to perform navigation experiments and to analyze the benefits of a sensor array over a single sensor in practice. As our experimental results show, navigation can be improved significantly by calibrating the IMU device regarding scale factors, offsets and cross-axis sensitivity. By comparing predicted navigation error and experimental results it is shown that gyroscope angle random walk and bias instability are dominant and therefore can be used to estimate naviaation performance. The latter improves roughly by a factor of $\\\\sqrt{14}$ when using an array of 14 devices instead of a single one. A Kalman Filter with motion constraints minimizes the error when estimating positions.\",\"PeriodicalId\":424028,\"journal\":{\"name\":\"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INERTIAL51137.2021.9430468\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INERTIAL51137.2021.9430468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

摘要

本文研究了使用冗余低成本MEMS传感器阵列的纯惯性导航的位置精度。一个精心设计的IMU被用来进行导航实验,并在实践中分析传感器阵列相对于单个传感器的优势。实验结果表明,通过对IMU设备的尺度因子、偏移量和跨轴灵敏度进行校准,可以显著提高导航性能。通过预测导航误差与实验结果的比较,表明陀螺仪角度随机游走和偏置不稳定性是主要因素,因此可以用来估计导航性能。当使用由14个设备组成的阵列而不是单个设备时,后者的性能大约提高了$\sqrt{14}$。带有运动约束的卡尔曼滤波器使估计位置时的误差最小化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Purely Inertial Navigation with a Low-Cost MEMS Sensor Array
This paper examines the position precision of purely inertial navigation using an array of redundant, low-cost MEMS sensors. A carefully designed IMU is used to perform navigation experiments and to analyze the benefits of a sensor array over a single sensor in practice. As our experimental results show, navigation can be improved significantly by calibrating the IMU device regarding scale factors, offsets and cross-axis sensitivity. By comparing predicted navigation error and experimental results it is shown that gyroscope angle random walk and bias instability are dominant and therefore can be used to estimate naviaation performance. The latter improves roughly by a factor of $\sqrt{14}$ when using an array of 14 devices instead of a single one. A Kalman Filter with motion constraints minimizes the error when estimating positions.
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