周跳探测在高精度GPS(global positioning system)数据处理中一直都是比较重要的环节.实际数据处理中可根据具体测量模式和需求采用已有的若干经典周跳探测方法,但单频非差相位观测值的周跳探测与修复则比较困难.为此提出一种新的周跳探测方法,它是基于灰色理论对伪距和载波相位观测值构造的周跳检验量进行建模,通过模型预测检验量的阈值范围对比实测值来判断是否发生周跳.通过对实测GPS静态数据在不同采样率下分别进行周跳探测与修复算例分析,结果表明对于高采样率的非差相位观测数据能够快速和准确地修复周跳,为非差精密定位提供了较好的数据质量控制.
Cycle slip detection is always an important section of global positioning system (GPS) precise data processing. Some classic methods about cycle slip detection are adopted in practical data processing, but for single-frequency un- differenced phase observations, cycle slip detection and modification are hard to be realized. A new cycle slip detection method is proposed on the basis of the grey theory to predict the threshold limit by modeling tests which are constructed by pseudo range and carrier phase observations. This algorithm is analyzed with different sampling rate GPS static observations. The results indicate that the algorithm can detect and correct outliers properly for high sampling rate observations, which helps data quality controlling for undifferenced precise positioning.