Attitude-Independent Magnetometer Calibration Based on Adaptive Filtering

Autor:	Wenshi Zeng, Lubin Chang, Junji Gao, Yude Tong, Qiang Bian
Rok vydání:	2022
Předmět:	Accuracy and precision Computer science Magnetometer ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Least squares Fluxgate compass law.invention Magnetic field Adaptive filter law Calibration Electrical and Electronic Engineering Instrumentation Algorithm
Zdroj:	IEEE Sensors Journal. 22:195-202
ISSN:	2379-9153 1530-437X
DOI:	10.1109/jsen.2021.3114347
Popis:	In order to calibrate the tri-axis magnetometer errors, an attitude-independent calibration method based on adaptive filtering is proposed. This method can estimate all the error parameters precisely without the need of external equipment to provide stable magnetic field and reference attitude information. In this paper, incremental meta-learning Incremental Delta-Bar-Delta (IDBD) algorithm is applied to adaptive filtering to achieve magnetometer calibration instead of the traditional least squares (LS) algorithm. The results of this calibration method will be compared with the classical calibration method in the earth’s magnetic field as well. The experiments show that the sensor error after calibration by the proposed method is significantly suppressed and reduced by more than 93 % compared with that before calibration and the calibration effect of IDBD algorithm is much better than that of LS algorithm. The proposed method in this paper can not only effectively improves the measurement accuracy of the tri-axis fluxgate sensor, but also is potentially applicable to various kinds of three-axis sensors.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4554ad32a4ce25d34e8b1a0f69a6a973 https://doi.org/10.1109/jsen.2021.3114347 Zobrazit plný text záznamu