TY - GEN
T1 - Accurate magnetic object localization using artificial neural network
AU - Chen, Shengzhi
AU - Zhu, Minghua
AU - Zhang, Qing
AU - Cai, Xuesong
AU - Bo, Xiao
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Magnetic object localization technology is emerging to bring substantial benefits for human medical investigation, such as tracking wireless endoscopic devices or catheters with embedded permanent magnets. Towards accurate magnetic localization, we propose a novel method of fitting the magnetic field intensity and magnetic gradient tensor (MGT) with artificial neural network (ANN) for magnetic object localization, which permits accurate localization of the magnetic object in a certain range. In the simulation, we analyzed and compared the capability of the proposed method and a traditional method based on tensor module gradient. The results show that the average localization error of the proposed method is at least 8 times more accurate than the traditional method in the noisy environment. Besides, a magnetic localization system based on a sensor array was used to carry out a localization experiment and the result has shown the feasibility of the proposed method with the average localization error of 2.15 cm when the magnetic target distance was from 61 to 79 cm.
AB - Magnetic object localization technology is emerging to bring substantial benefits for human medical investigation, such as tracking wireless endoscopic devices or catheters with embedded permanent magnets. Towards accurate magnetic localization, we propose a novel method of fitting the magnetic field intensity and magnetic gradient tensor (MGT) with artificial neural network (ANN) for magnetic object localization, which permits accurate localization of the magnetic object in a certain range. In the simulation, we analyzed and compared the capability of the proposed method and a traditional method based on tensor module gradient. The results show that the average localization error of the proposed method is at least 8 times more accurate than the traditional method in the noisy environment. Besides, a magnetic localization system based on a sensor array was used to carry out a localization experiment and the result has shown the feasibility of the proposed method with the average localization error of 2.15 cm when the magnetic target distance was from 61 to 79 cm.
KW - Artificial neural network
KW - Localization
KW - Magnetic dipole
KW - Magnetic gradient tensor
UR - https://www.scopus.com/pages/publications/85084292744
U2 - 10.1109/MSN48538.2019.00019
DO - 10.1109/MSN48538.2019.00019
M3 - 会议稿件
AN - SCOPUS:85084292744
T3 - Proceedings - 2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2019
SP - 25
EP - 30
BT - Proceedings - 2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2019
Y2 - 11 December 2019 through 13 December 2019
ER -