[1] Wang Dongsheng, Wang Yan, Zhou Ying, Jiang Guoping, et al. Sensor fusion for heading angle estimationbased on random forest algorithm [J]. Journal of Southeast University (English Edition), 2021, 37 (2): 192-198. [doi:10.3969/j.issn.1003-7985.2021.02.009]

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Sensor fusion for heading angle estimationbased on random forest algorithm()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

37

Issue:

2021 2

Page:

192-198

Research Field:

Automation

Publishing date:

2021-06-20

Info

Title:

Sensor fusion for heading angle estimationbased on random forest algorithm

Author(s):

Wang Dongsheng;  Wang Yan;  Zhou Ying;  Jiang Guoping

School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Keywords:

magnetometer;  inertial measurement unit;  fusion;  heading angle;  magnetic interference

PACS:

TP212.9

DOI:

10.3969/j.issn.1003-7985.2021.02.009

Abstract:

To improve the accuracy of the calculation of a heading angle under magnetic interference, magnetometers and inertial measurement units(IMUs)were fused. The observation value of the heading angle was deduced on the basis of the modeling of the magnetometer error and the analysis of the relation of the magnetometer triaxial output and the distribution characteristics of the magnetic field at two adjacent time periods. Meanwhile, the gyro state and angular velocity increment were used as the basis of the IMU to calculate the prediction value of the heading angle. With the changes in the heading angle and environmental interference, a random forest(RF)algorithm was used to iteratively calculate the weights to fuse the observation value of the heading angle based on the magnetometer and the prediction value of the heading angle based on the IMU. The results show that relative to the common sensor fusion method, the proposed sensor fusion method based on the RF algorithm achieved an approximate 60% improvement in heading angle accuracy. Hence, the proposed method can effectively improve the accuracy of the heading angle under magnetic interference by using an RF algorithm to calculate the output weights of the magnetometer and IMU.

References:

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Memo

Memo:

Biography: Wang Dongsheng(1983—), male, doctor, associate professor, wangdongsheng@njupt.edu.cn.
Foundation item: The National Natural Science Foundation of China(No. 51708299).
Citation: Wang Dongsheng, Wang Yan, Zhou Ying, et al. Sensor fusion for heading angle estimation based on random forest algorithm[J].Journal of Southeast University(English Edition), 2021, 37(2):192-198.DOI:10.3969/j.issn.1003-7985.2021.02.009.

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