Neural inertial navigation system on pedestrian

doi:10.1088/1361-6501/ace377

	Neural inertial navigation system on pedestrian
	Huang, Fengrong 1; Gao, Min 1; Liu, Qinglin 1; Tang, Fulin2 ; Wu, Yihong2
发表期刊	MEASUREMENT SCIENCE AND TECHNOLOGY
ISSN	0957-0233
	2023-10-01
卷号	34 期号:10 页码:14
通讯作者	Tang, Fulin(gl2022312@163.com)
摘要	The recent research shows that data-driven inertia navigation technology can significantly alleviate the drift error of micro-electro-mechanical system inertial measurement unit (MEMS-IMU) in pedestrian localization. However, most existing methods must rely on attitude information provided by external procedure (such as smartphone API), which violates the original intention of full autonomy of inertial navigation, and attitude information is also inaccurate. To address the problem, we propose a pedestrian indoor neural inertial navigation system that does not rely on external information and is only based on low-cost MEMS-IMU. First, a deep learning based neural inertial network was designed to estimate attitude. Then, in order to obtain position estimation with both global and local accuracy, an invariant extended Kalman filter (IEKF) framework was proposed, where 3D displacement and its uncertainty regressed by a deep residual network are utilized to update IEKF. Extensive experimental results on a public dataset and a self-collected dataset show that the proposed method provides accurate attitude estimation and outperforms state-of-the-art methods in position estimation, demonstrating the superiority of our method in reliability and accuracy.
关键词	localization deep learning pedestrian indoor navigation IEKF inertial navigation
DOI	10.1088/1361-6501/ace377
关键词[WOS]	ORIENTATION-ESTIMATION
收录类别	SCI
语种	英语
WOS研究方向	Engineering ; Instruments & Instrumentation
WOS类目	Engineering, Multidisciplinary ; Instruments & Instrumentation
WOS记录号	WOS:001026182000001
出版者	IOP Publishing Ltd
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53625
专题	多模态人工智能系统全国重点实验室
通讯作者	Tang, Fulin
作者单位	1.Hebei Univ Technol, Sch Mech Engn, Tianjin 300400, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Huang, Fengrong,Gao, Min,Liu, Qinglin,et al. Neural inertial navigation system on pedestrian[J]. MEASUREMENT SCIENCE AND TECHNOLOGY,2023,34(10):14.
APA	Huang, Fengrong,Gao, Min,Liu, Qinglin,Tang, Fulin,&Wu, Yihong.(2023).Neural inertial navigation system on pedestrian.MEASUREMENT SCIENCE AND TECHNOLOGY,34(10),14.
MLA	Huang, Fengrong,et al."Neural inertial navigation system on pedestrian".MEASUREMENT SCIENCE AND TECHNOLOGY 34.10(2023):14.