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A novel geomagnetic measurement calibration algorithm based on neural networks

机译:基于神经网络的地磁测量标定新算法

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The studying of the geomagnetic field is a fundamental task in geomagnetism navigation and observation. But the magnetometer measurements are usually susceptible to the environmental magnetic field as well as the carrier magnetic field. Therefore a calibration method to the magnetic disturbance is of great significance in practical high-precision measurements. This paper conducts in-depth analysis about the magnetic interference in geomagnetic measurements, and then concerning the characteristics of the magnetic interference, designs and sets up a calibration algorithm based on the BP neural network algorithm. This algorithm can be effective to identify the dynamic characteristics and non-linear problems about the system, and obtain the mapping relationship of the input - output function, with a strong adaptive ability, a high rate of accuracy-time and an effective calibration result.
机译:地磁场的研究是地磁导航和观测的基本任务。但是磁力计的测量通常容易受到环境磁场以及载体磁场的影响。因此,针对磁干扰的校准方法在实际的高精度测量中具有重要意义。本文对地磁测量中的电磁干扰进行了深入的分析,然后针对电磁干扰的特征进行了研究,设计并建立了基于BP神经网络算法的标定算法。该算法可以有效地识别系统的动态特性和非线性问题,获得输入-输出函数的映射关系,具有较强的自适应能力,较高的准确率和有效的校正结果。

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