Multiscale Transformer and Attention Mechanism for Magnetic Spatiotemporal Sequence Localization
文献类型：期刊论文
| 作者 | Wang, Qu1,2; Wang, Liying3; Fu, Meixia1; Wang, Jianquan1; Sun, Lei1; Huang, Rong4; Li, Xianda4; Jiang, Zhuqing5; Luo, Haiyong6 |
| 刊名 | IEEE INTERNET OF THINGS JOURNAL
 |
| 出版日期 | 2024-06-01 |
| 卷号 | 11期号:11页码:19454-19469 |
| 关键词 | Indoor positioning Internet of Things (IoT) magnetic positioning magnetometer calibration |
| ISSN号 | 2327-4662 |
| DOI | 10.1109/JIOT.2024.3365793 |
| 英文摘要 | Location-based service (LBS) is the core of Internet of Things (IoT), which serves tracking, navigation, and monitoring. The ubiquitous magnetic signals are temporally stable and spatially distinguishable and can achieve high-precision and ubiquitous positioning results without additional infrastructure, which is favored by researchers and has become a major research hotspot. Although there has been extensive research in the field of indoor magnetic positioning, there is still room for optimization in terms of positioning accuracy and robustness. Aiming at the problem that the magnetometer is offset and susceptible to environmental interference, we propose an online magnetometer calibration algorithm without user perception. Aiming at the inconsistency of magnetic data spatial scale problem caused by differences in device sampling frequency and user walking speed, we leverage different scales to segment the magnetic data, extract the magnetic sequence features of the corresponding scales through Transformer, utilize the attention mechanism to score the weights of the different scale features, and finally fuse the multiple scale features for positioning. We conduct extensive and well-designed experiments on public data sets and self-collected data sets. The experimental results indicate that the proposed method effectively solves the magnetic spatial scale problem and improves indoor magnetic positioning accuracy. |
| 资助项目 | National Key Research and Development Program[2020YFB1708800] ; China Postdoctoral Science Foundation[2021M700385] ; Guang Dong Basic and Applied Basic Research Foundation[2024A1515011866] ; Guang Dong Basic and Applied Basic Research Foundation[2021A1515110577] ; Central Guidance on Local Science and Technology Development Fund of Shan Xi Province[YDZJSX2022B019] ; Central Guidance on Local Science and Technology Development Fund of Shan Xi Province[YDZJSX20231D005] ; National Natural Science Foundation of China[61872046] ; National Natural Science Foundation of China[62002026] ; Joint Research Fund for Beijing Natural Science Foundation and Haidian Original Innovation[L232001] ; University of Science and Technology Beijing Young Faculty International Exchange and Development Program[QNXM20230016] ; Fundamental Research Funds for Central Universities[FRF-MP-20-37] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:001285460000091 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/39667]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Wang, Jianquan; Luo, Haiyong |
| 作者单位 | 1.Univ Sci & Technol Beijing, Sch Automat Sci & Elect Engn, Beijing 100083, Peoples R China 2.Univ Sci & Technol Beijing, Shunde Grad Sch, Foshan 528399, Peoples R China 3.Technol Ctr Qihoo 360 Technol Co Ltd, Intelligent Recommendat Grp, Search Div, Beijing 100015, Peoples R China 4.Res Inst China Unicom, Comp & Network Res Dept, Beijing 100190, Peoples R China 5.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China 6.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Qu,Wang, Liying,Fu, Meixia,et al. Multiscale Transformer and Attention Mechanism for Magnetic Spatiotemporal Sequence Localization[J]. IEEE INTERNET OF THINGS JOURNAL,2024,11(11):19454-19469. |
| APA | Wang, Qu.,Wang, Liying.,Fu, Meixia.,Wang, Jianquan.,Sun, Lei.,...&Luo, Haiyong.(2024).Multiscale Transformer and Attention Mechanism for Magnetic Spatiotemporal Sequence Localization.IEEE INTERNET OF THINGS JOURNAL,11(11),19454-19469. |
| MLA | Wang, Qu,et al."Multiscale Transformer and Attention Mechanism for Magnetic Spatiotemporal Sequence Localization".IEEE INTERNET OF THINGS JOURNAL 11.11(2024):19454-19469. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。