周期干扰对矢量磁强计标定过程的影响

T. Kliment, M. Krchňák, Ž. Miženková, P. Lipovský
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引用次数: 1

摘要

本文的目的是证明即使在有外部干扰的条件下,使用神经网络也可以校准三维矢量磁强计,从而消除了选择环境的要求。此外,所选择的校准方法与位置无关,因此不需要定位装置。考虑到所选HMC 5883L传感器的主要系统误差,选择了考虑乘性、加性和正交性的逆模型。校准最初在实验室进行,没有额外的干扰。其次,在附加周期谐波干扰的环境下进行标定,并对标定结果进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Influence of periodical interference on calibration process of vector magnetometer
The aim of the article is to demonstrate that calibration of 3D vector magnetometers using neural networks is possible even in the conditions with external interferences, eliminating the requirement to choose environment. In addition, the selected calibration method is position-independent and therefore no positioning devices are necessary. Given the dominant systematic errors of the selected HMC 5883L sensor an inverse model that takes into account the multiplicative, additive and orthogonality was elected. Calibration was performed initially in the laboratory without additional interference. Next, calibration took place in the environment with additional periodic harmonic disturbance and the results were compared.
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