TY - GEN
T1 - A Radio Tomographic Imaging Method Using Channel State Information and Image Fusion
AU - Sun, Cheng
AU - Gao, Fei
AU - Liu, Heng
AU - Xu, Shengxin
AU - An, Jianping
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/26
Y1 - 2018/9/26
N2 - Indoor radio tomographic imaging (RTI) is a cutting-edge technology, which could reconstruct the cross-sectional image of an object within the monitored area. It builds imaging procedure by analyzing the effects of objects on surrounding wireless signals. Channel state information (CSI) provides the amplitude and phase information on each sub-carrier for every transmit-receive antenna pairs. Compared with received signal strength (RSS), CSI could provide finer-grained and abundant channel measurements. In this paper, we propose a CSI-RTI system. Specifically, we separately analyze the amplitude and phase information of CSI to get the influence mechanism of the person on them, and then a CSI mixed imaging approach is proposed to construct an image on each antenna pair. Finally, we propose a wireless indoor imaging scheme based on image fusion to deal with the situation of multiple antenna pairs. Experimental results are compared with the RSS-based radio tomographic imaging approach, the imaging accuracy and localization performance have been improved.
AB - Indoor radio tomographic imaging (RTI) is a cutting-edge technology, which could reconstruct the cross-sectional image of an object within the monitored area. It builds imaging procedure by analyzing the effects of objects on surrounding wireless signals. Channel state information (CSI) provides the amplitude and phase information on each sub-carrier for every transmit-receive antenna pairs. Compared with received signal strength (RSS), CSI could provide finer-grained and abundant channel measurements. In this paper, we propose a CSI-RTI system. Specifically, we separately analyze the amplitude and phase information of CSI to get the influence mechanism of the person on them, and then a CSI mixed imaging approach is proposed to construct an image on each antenna pair. Finally, we propose a wireless indoor imaging scheme based on image fusion to deal with the situation of multiple antenna pairs. Experimental results are compared with the RSS-based radio tomographic imaging approach, the imaging accuracy and localization performance have been improved.
KW - channel state information
KW - eigenvectors and eigenfunctions
KW - image fusion
KW - kernel distance
KW - radio tomographic imaging
UR - https://www.scopus.com/pages/publications/85055861999
U2 - 10.1109/ICEIEC.2018.8473507
DO - 10.1109/ICEIEC.2018.8473507
M3 - Conference contribution
AN - SCOPUS:85055861999
T3 - Proceedings of 2018 IEEE 8th International Conference on Electronics Information and Emergency Communication, ICEIEC 2018
SP - 223
EP - 227
BT - Proceedings of 2018 IEEE 8th International Conference on Electronics Information and Emergency Communication, ICEIEC 2018
A2 - Wenzheng, Li
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2018
Y2 - 15 June 2018 through 17 June 2018
ER -