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Multimodal Data fusion for SRGPS antenna motion error reduction

机译：用于减少SRGPS天线运动误差的多峰数据融合

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摘要

Antenna motion is a primary fault that degrades the integrity of shipboard relative GPS (SRGPS) systems, so we must investigate how to monitor and mitigate its impacts. Previous work proposed a single-baseline mode, but it had obvious problems, such as large motion errors, error measurement difficulties, and poor reliability. To solve these issues, we propose a multiple reference station architecture that deploys more than one reference station at different positions on ship. The observations are first translated to the ship reference point, and then integrated into a comprehensive measurement that accounts for the overall antenna motion errors. We consider two integrating methods: direct and weighted average methods. The direct average method is simple and intuitive, but the weighted average method more effectively reduced the overall antenna motion error by using the reciprocal standard deviation of historical measurements as weighting factors. All the antennas are mounted on the same ship body, so their correlations should also be considered when determining weighting factors. We used the ranking scores of the antennas derived using a graph-learning algorithm and fused them with the standard deviations to create new weighting factors. Finally, our experimental results demonstrated that the weighting factors based on the standard deviations and ranking scores reduced the overall antenna-motion error variance and improved the system integrity.
机译：天线运动是导致舰船相对GPS（SRGPS）系统完整性下降的主要故障，因此我们必须研究如何监视和减轻其影响。先前的工作提出了单基线模式，但是它存在明显的问题，例如运动误差大，误差测量困难以及可靠性差。为了解决这些问题，我们提出了一种多参考站架构，该构架在船上的不同位置部署了多个参考站。首先将观测结果转换到船舶参考点，然后将其集成到一个综合测量中，以解决总体天线运动误差。我们考虑两种积分方法：直接法和加权平均法。直接平均法很简单直观，但是加权平均法通过使用历史测量值的倒数标准偏差作为加权因子，可以更有效地减少总体天线运动误差。所有天线都安装在同一船体上，因此在确定加权系数时也应考虑它们的相关性。我们使用通过图学习算法得出的天线的排名得分，并将它们与标准偏差相融合，以创建新的加权因子。最后，我们的实验结果表明，基于标准偏差和排名得分的加权因子减少了总体天线运动误差方差，并改善了系统完整性。

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