TY - JOUR
T1 - A survey on fusion-based indoor positioning
AU - Guo, Xiansheng
AU - Ansari, Nirwan
AU - Hu, Fangzi
AU - Shao, Yuan
AU - Elikplim, Nkrow Raphael
AU - Li, Lin
N1 - Funding Information:
Manuscript received March 18, 2019; revised August 27, 2019; accepted October 23, 2019. Date of publication November 1, 2019; date of current version March 11, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61371184, Grant 61671137, Grant 61771114, and Grant 61771316, and in part by the Application Foundation Projects of Science and Technology Department in Sichuan Province under Grant 2018JY0242 and Grant 2018JY0218. (Corresponding author: Xiansheng Guo.) X. Guo, F. Hu, Y. Shao, and L. Li are with the Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China (e-mail: xsguo@uestc.edu.cn; erguihu@gmail.com; shaoyuan_alison@163.com; nkrowraph@gmail.com; linli9419@gmail.com).
Publisher Copyright:
© 1998-2012 IEEE.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Demands for indoor positioning based services (IPS) in commercial and military fields have spurred many positioning systems and techniques. Complex electromagnetic environments (CEEs) may, however, degenerate the accuracy and robustness of some existing single systems and techniques. To overcome this drawback, fusion-based positioning of multiple systems and/or techniques have been proposed to revamp the positioning performance in CEEs. In this paper, we survey the fusion-based indoor positioning techniques and systems from seminal works to elicit the state of the art within our proposed unified fusion-based positioning framework, which consists of three fusion characteristics: source, algorithm, and weight spaces. Different from other surveys, this survey summarizes and analyzes the existing fusion-based positioning systems and techniques from three characteristics. Meanwhile, discussions in terms of lessons, challenges, and countermeasures are also presented. This survey is invaluable for researchers to acquire a clear concept of indoor fusion-based positioning systems and techniques and also to gain insights from this survey to further develop other advanced fusion-based positioning systems and techniques in the future.
AB - Demands for indoor positioning based services (IPS) in commercial and military fields have spurred many positioning systems and techniques. Complex electromagnetic environments (CEEs) may, however, degenerate the accuracy and robustness of some existing single systems and techniques. To overcome this drawback, fusion-based positioning of multiple systems and/or techniques have been proposed to revamp the positioning performance in CEEs. In this paper, we survey the fusion-based indoor positioning techniques and systems from seminal works to elicit the state of the art within our proposed unified fusion-based positioning framework, which consists of three fusion characteristics: source, algorithm, and weight spaces. Different from other surveys, this survey summarizes and analyzes the existing fusion-based positioning systems and techniques from three characteristics. Meanwhile, discussions in terms of lessons, challenges, and countermeasures are also presented. This survey is invaluable for researchers to acquire a clear concept of indoor fusion-based positioning systems and techniques and also to gain insights from this survey to further develop other advanced fusion-based positioning systems and techniques in the future.
KW - Indoor positioning based services (IPS)
KW - complex electromagnetic environments (CEEs)
KW - ensemble learning
KW - fusion-based positioning
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U2 - 10.1109/COMST.2019.2951036
DO - 10.1109/COMST.2019.2951036
M3 - Article
AN - SCOPUS:85074599324
SN - 1553-877X
VL - 22
SP - 566
EP - 594
JO - IEEE Communications Surveys and Tutorials
JF - IEEE Communications Surveys and Tutorials
IS - 1
M1 - 8889728
ER -