Adaptive Kalman filtering-based pedestrian navigation algorithm for smartphones

doi:10.1177/1729881420930934

	Adaptive Kalman filtering-based pedestrian navigation algorithm for smartphones
	Yu, Chen 1; Luo, Haiyong 2; Fang, Zhao 1; Qu, Wang 1; Shao, Wenhua 1
	2020-05-01
发表期刊	INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
ISSN	1729-8814
卷号	17 期号:3 页码:14
摘要	Pedestrian navigation with daily smart devices has become a vital issue over the past few years and the accurate heading estimation plays an essential role in it. Compared to the pedestrian dead reckoning (PDR) based solutions, this article constructs a scalable error model based on the inertial navigation system and proposes an adaptive heading estimation algorithm with a novel method of relative static magnetic field detection. To mitigate the impact of magnetic fluctuation, the proposed algorithm applies a two-way Kalman filter process. Firstly, it achieves the historical states with the optimal smoothing algorithm. Secondly, it adjusts the noise parameters adaptively to reestimate current attitudes. Different from the pedestrian dead reckoning-based solution, the error model system in this article contains more state information, which means it is more sensitive and scalable. Moreover, several experiments were conducted, and the experimental results demonstrate that the proposed heading estimation algorithm obtains better performance than previous approaches and our system outperforms the PDR system in terms of flexibility and accuracy.
关键词	Pedestrian navigation error model system inertial sensors integration magnetic field heading estimation
DOI	10.1177/1729881420930934
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program[2019YFC1511400] ; Action Plan Project of the Beijing University of Posts and Telecommunications - Fundamental Research Funds for the Central Universities[2019XD-A06] ; Special Project for Youth Research and Innovation, Beijing University of Posts and Telecommunications ; Fundamental Research Funds for the Central Universities[2019PTB-011] ; National Natural Science Foundation of China[61872046] ; National Natural Science Foundation of China[61761038] ; Beijing Natural Science Foundation[L192004] ; Haidian Original Innovation[L192004] ; Key Research and Development Project from Hebei Province[19210404D] ; Science and Technology Plan Project of Inner Mongolia Autonomous Regio[2019GG328] ; Open Project of the Beijing Key Laboratory of Mobile Computing and Pervasive Device
WOS研究方向	Robotics
WOS类目	Robotics
WOS记录号	WOS:000544697500001
出版者	SAGE PUBLICATIONS INC
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/15086
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Yu, Chen
作者单位	1.Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Yu, Chen,Luo, Haiyong,Fang, Zhao,et al. Adaptive Kalman filtering-based pedestrian navigation algorithm for smartphones[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2020,17(3):14.
APA	Yu, Chen,Luo, Haiyong,Fang, Zhao,Qu, Wang,&Shao, Wenhua.(2020).Adaptive Kalman filtering-based pedestrian navigation algorithm for smartphones.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,17(3),14.
MLA	Yu, Chen,et al."Adaptive Kalman filtering-based pedestrian navigation algorithm for smartphones".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 17.3(2020):14.