利用等面积格网模型的GNSS PDOP高效评估方法

为解决位置精度衰减因子( position dilution of precision, PDOP )监测评估中经常使用的等经纬度间隔格网模型（equal-interval of longitude and latitude grid, GRID_ELL）存在全球格网点分布不合理、评估统计结果有偏差、计算和存储效率低等问题，进一步开展全球PDOP长周期实时监测服务，引入两种等面积格网模型：等弧长格网模型（equal-arch-length grid, GRID_EAL）和正二十面体球面格网模型( icosahedron-based grid, GRID_IB )，并分析其与GRID_ELL模型之间的差异。结果表明，两种等面积格网模型能够显著改善GRID_ELL模型全球格网点分布不均匀的现象以及目前全球PDOP监测评估统计结果中的偏差。重点针对不同格网间距的GRID_EAL模型适用性进行测试，结果表明，5°间隔的GRID_EAL模型能在保持全球PDOP监测评估准确性的同时，在计算效率和存储上带来36.3%和34.1%的提升与优化。

An Efficient Method for GNSS PDOP Assessment by Using Equal-Area Grid Models

To solve the problems of unreasonable distribution of global grid points, biased statistical results and low calculation and storage efficiency of the equal-arch-length grid (GRID_ELL), which is often used in position dilution of precision (PDOP) monitoring and evaluation, we introduce the equal-arch-length grid (GRID_EAL) and the icosahedron-based grid (GRID_IB) to further develop the global PDOP long-period real-time monitoring service. We analyze the differences between them and the GRID_ELL model. The results show that the two equal-area grid models can significantly improve the uneven distribution of global grid points in the GRID_ELL model and the bias in the current global PDOP monitoring assessment statistics. Focusing on the applicability of the GRID_EAL model with different grid spacing, the results show that the GRID_EAL model with 5° spacing can bring 36.3% and 34.1% improvement and optimization in its computational efficiency and storage while maintaining the accuracy of the global PDOP monitoring assessment.