一种数字磁罗盘全罗差自主优化补偿方法
发布时间：2018-09-16 19:00
【摘要】：为了进一步提高数字磁罗盘全姿态罗差补偿精度,提出了一种基于地磁场分量的罗差自主优化补偿方法。从罗差补偿模型出发,分析椭球拟合补偿方法的局限性,在对参数缺失和剩余误差分析的基础上,建立了包含缺失参数的优化补偿模型;针对非线性优化模型引入粒子群算法PSO(Particle Swarm Optimization)对模型参数进行估计,数值仿真结果证明了算法可有效估计缺失参数。实验结果表明,优化补偿过程无需借助外部辅助姿态信息,俯仰角-20°姿态下,优化补偿方法在椭球假设补偿基础上将其最大误差由4.8°降至1.9°,误差标准差由1.5°降至1.1°。
[Abstract]:In order to improve the precision of all-attitude offset compensation of digital magnetic compass, an autonomous compensation method based on geomagnetic field component is proposed. The limitation of ellipsoid fitting compensation method is analyzed based on the Luo difference compensation model. Based on the analysis of the missing parameters and residual errors, the optimal compensation model including missing parameters is established. The particle swarm optimization (PSO (Particle Swarm Optimization) algorithm is introduced to estimate the parameters of the nonlinear optimization model. The numerical simulation results show that the algorithm can effectively estimate the missing parameters. The experimental results show that the optimal compensation method reduces the maximum error from 4.8 掳to 1.9 掳and the error standard deviation from 1.5 掳to 1.1 掳on the basis of ellipsoid assumption.
【作者单位】： 南京理工大学机械工程学院;
【分类号】：TN965
，
本文编号：2244474
[Abstract]:In order to improve the precision of all-attitude offset compensation of digital magnetic compass, an autonomous compensation method based on geomagnetic field component is proposed. The limitation of ellipsoid fitting compensation method is analyzed based on the Luo difference compensation model. Based on the analysis of the missing parameters and residual errors, the optimal compensation model including missing parameters is established. The particle swarm optimization (PSO (Particle Swarm Optimization) algorithm is introduced to estimate the parameters of the nonlinear optimization model. The numerical simulation results show that the algorithm can effectively estimate the missing parameters. The experimental results show that the optimal compensation method reduces the maximum error from 4.8 掳to 1.9 掳and the error standard deviation from 1.5 掳to 1.1 掳on the basis of ellipsoid assumption.
【作者单位】： 南京理工大学机械工程学院;
【分类号】：TN965
，
本文编号：2244474
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