Calibration of three-axis strapdown magnetometers using Particle Swarm Optimization algorithm

Zhitian Wu, Yuanxin Wu, Xiaoping Hu, Mei-ping Wu
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引用次数: 20

Abstract

In this work a new algorithm is developed for onboard calibration of three-axis strapdown magnetometers. The sensor errors, namely hard iron, soft iron, nonorthogonality, scale factors, biases and among others are taken into account. Particle Swarm Optimization (PSO) strategy is applied to estimate the errors above. The advantages of this method are no need for good initial values or linearization, easy realization and fast convergence. Accuracy and robustness of the proposed algorithm are validated by experiments. The post-calibration residuals are down to less than 10nT compared with approximate 1000nT before calibration. The proposed algorithm yields robust results with sufficient accuracy in tests.
基于粒子群优化算法的三轴捷联磁力计标定
本文提出了一种新的三轴捷联式磁强计板载标定算法。传感器误差,即硬铁、软铁、非正交性、尺度因素、偏差等。采用粒子群优化(PSO)策略对上述误差进行估计。该方法不需要良好的初始值和线性化,易于实现,收敛速度快。实验验证了该算法的准确性和鲁棒性。校正后的残差低于10nT,而校正前的残差约为1000nT。该算法在测试中获得了具有足够精度的鲁棒性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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