Magnetic Dipole Object Tracking Algorithm Based on Magnetometer Array in Geomagnetic Background

Luzhao CHEN; Yongqiang FENG; Ruijie GUO; Wanhua ZHU; Guangyou FANG

doi:10.11999/JEIT190236

Volume 42 Issue 3

Mar. 2020

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Article Navigation > Journal of Electronics & Information Technology > 2020 > 42(3): 573-581

Luzhao CHEN, Yongqiang FENG, Ruijie GUO, Wanhua ZHU, Guangyou FANG. Magnetic Dipole Object Tracking Algorithm Based on Magnetometer Array in Geomagnetic Background[J]. Journal of Electronics & Information Technology, 2020, 42(3): 573-581. doi: 10.11999/JEIT190236

Citation:

Luzhao CHEN, Yongqiang FENG, Ruijie GUO, Wanhua ZHU, Guangyou FANG. Magnetic Dipole Object Tracking Algorithm Based on Magnetometer Array in Geomagnetic Background[J]. Journal of Electronics & Information Technology, 2020, 42(3): 573-581. doi: 10.11999/JEIT190236

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Magnetic Dipole Object Tracking Algorithm Based on Magnetometer Array in Geomagnetic Background

doi: 10.11999/JEIT190236

Luzhao CHEN^{1, 2, 3},
Yongqiang FENG^{1, 2},
Ruijie GUO³,
Wanhua ZHU^{1
,
,},
Guangyou FANG¹

1.
Key Laboratory of Electromagnetic Radiation and Sensing Technology, Chinese Academy of Sciences, Beijing 100190, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Beijing Automation Control Equipment Institute, Beijing 100074, China

Funds: The Youth Program of National Natural Science Foundation of China (41704177), The National Key R&D Program of China (2018YFC0603201)

Received Date: 2019-04-10
Rev Recd Date: 2019-12-01

Available Online: 2019-12-09

Publish Date: 2020-03-19

Abstract

Abstract

In order to solve the problem of geomagnetic interference and model nonlinearity in the tracking process of magnetic dipole under geomagnetic background, Monte Carlo Kalman Filter (MCKF) tracking method based on differential magnetic anomaly is proposed in this paper. The new tracking method takes the difference of magnetic field measured by sensor array as the observation signal, and uses Monte Carlo Kalman Filtering (MCKF) algorithm to solve the nonlinear problem of the model to realize the real-time tracking of magnetic dipole targets. The simulation results show that the proposed method is more accurate than the traditional Extended Kalman Filter (EKF) or Untracked Kalman Filter (UKF) in the stable tracking process. The results of real geomagnetic background tracking experiments show that the proposed algorithm has better tracking performance under low SNR.
- Magnetic dipole,
- Monte Carlo Kalman Filter (MCKF),
- Sensor array,
- Geomagnetic background

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References(23)

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