Analysis of the upper bounds for the integer ambiguity validation statistics
Analysis of the upper bounds for the integer ambiguity validation statistics
复制标题
DOI：
10.1007/s10291-013-0312-1
复制
发表时间：
2013
期刊：
影响因子：
4.9
通讯作者：
Tao Li;Jinling Wang
中科院分区：
文献类型：
--
作者：
Tao Li;Jinling Wang
整数模糊度验证是全球卫星导航系统（GNSS）高精度定位导航的重要质量控制步骤。为了验证已解决的整数歧义，统计测试，如热比测试，f比测试，w比测试，差异测试和投影测试，已得到青睐。在实践中，这些统计检验的临界值要么由经验决定，要么由假设的分布决定。然而，先前的研究表明，其中一些统计数据有上限，可以从模拟中获得。在这篇贡献中，我们发现在整数孔径估计的框架下，这些模糊度验证统计测试的上界可以在没有实际测量或模拟的情况下推导出来。因此，这些统计检验的假设分布是不合适的。由推导可知，这些模糊度验证测试的上界仅依赖于模糊度几何（如浮动模糊度方差-协方差矩阵），可以在GNSS定位设计阶段获得。因此，这些模糊度验证统计的临界值有一个严格的范围，应该选择小于先验推导的上限。否则，不能得到整数二义性。
Integer ambiguity validation is an essential quality control step for high-precision positioning and navigation with global navigation satellite systems (GNSS). In order to validate the resolved integer ambiguities, statistical tests, such as theR-ratio test,F-ratio test,W-ratio test, difference test, and projector test, have been favored. In practice, the critical values for these statistical tests are determined either empirically or from the assumed distributions. However, previous research has revealed that some of these statistics have upper bounds, which can be obtained from simulations. In this contribution, we find that under the framework of the integer aperture estimation, the upper bounds for these ambiguity validation statistical tests can be derived without actual measurements or simulation. As a result, the assumed distributions for these statistical tests are inappropriate. According to the derivation, it has been concluded that the upper bounds of these ambiguity validation tests depend only on the ambiguity geometry (e.g., the float ambiguity variance–covariance matrix) and can be obtained at the design stage of GNSS positioning. Thus, the critical value for these ambiguity validation statistics has a rigorous range, and it should be chosen to be smaller than a priori derived upper bound. Otherwise, no integer ambiguities can be obtained.