基于抽样理论的改进型星座覆盖分析方法

Improved Constellation Coverage Analysis Method Based on Sampling Theory

摘要:

针对传统网格点方法在分析星座对目标区域的覆盖性能时,存在着计算效率不高的问题,利用抽样理论中借助样本统计量对总体参数进行估计的思想,对传统网格点方法加以了改进;通过分析星座对目标区域内所有网格点的覆盖情况与网格点经纬度之间的关系,确立了对所有网格点构成的总体采用先分层后随机的抽样方式,并分析了层的划分和样本量在各层的分配；根据不同指标的统计特征,给出了不同星座覆盖性能指标的估计方法和不同精度条件下总样本量的计算过程,并建立了改进网格点法的实施流程；最后利用改进方法计算了仿真时段内北斗卫星导航系统对某一地面区域的平均PDOP值,通过与传统网格点方法的仿真结果进行比较并对仿真数据进行分析,证明了该改进方法在保证计算精度的同时,有效地提升了计算效率。

Abstract:

In view of the problem of low computational efficiency of traditional grid point method when analyze the constellation coverage performance of target area,the traditional grid point method is improved by using the idea of estimating population parameters through sample statistics in sampling theory.Through analyzing the relationship between the constellation coverage performance of all grid points in the target area and grid points’ latitude and longitude, the stratified random sampling method was established, the layer division method and the distribution way of sample size in each layer are researched.According to the statistical characteristics of different indexes,the improved grid point method gives the way to estimate different coverage performance indexes of constellation and calculate the number of grids with different precision, the process of the improved grid point method is also established. Finally, the average PDOP value of the target region of the Beidou satellite navigation system is calculated through the improved method, by comparing the simulation results with the traditional grid point method, it is proved that the improved method can significantly improve the computational efficiency while ensuring the accuracy of calculation.