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Cycle slip detection and repair for undifferenced GPS observations under high ionospheric activity

机译:高电离层活动下无差异GPS观测的周期滑动检测和修复

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摘要

We develop a new approach for cycle slip detection and repair under high ionospheric activity using undifferenced dual-frequency GPS carrier phase observations. A forward and backward moving window averaging (FBMWA) algorithm and a second-order, time-difference phase ionospheric residual (STPIR) algorithm are integrated to jointly detect and repair cycle slips. The FBMWA algorithm is proposed to detect cycle slips from the widelane ambiguity of Melbourne-Wübbena linear combination observable. The FBMWA algorithm has the advantage of reducing the noise level of widelane ambiguities, even if the GPS data are observed under rapid ionospheric variations. Thus, the detection of slips of one cycle becomes possible. The STPIR algorithm can better remove the trend component of ionospheric variations compared to the normally used first-order, time-difference phase ionospheric residual method. The combination of STPIR and FBMWA algorithms can uniquely determine the cycle slips at both GPS L_1 and L_2 frequencies. The proposed approach has been tested using data collected under different levels of ionospheric activities with simulated cycle slips. The results indicate that this approach is effective even under active ionospheric conditions.
机译:我们使用无差异的双频GPS载波相位观测,开发了一种在高电离层活动下进行循环滑动检测和修复的新方法。将前进和后退移动窗口平均算法(FBMWA)和二阶时差相位电离层残差(STPIR)算法集成在一起,共同检测和修复周跳。提出了FBMWA算法,以从可观察到的Melbourne-Wübbena线性组合的宽模糊度检测周期滑移。即使在快速电离层变化下观测到GPS数据的情况下,FBMWA算法也具有降低宽模糊度噪声水平的优势。因此,可以检测到一个周期的滑动。与通常使用的一阶时差相位电离层残差方法相比,STPIR算法可以更好地消除电离层变化的趋势分量。 STPIR和FBMWA算法的结合可以唯一确定GPS L_1和L_2频率下的周跳。已使用在模拟电离层的不同电离层活动水平下收集的数据对所提出的方法进行了测试。结果表明,即使在电离层活跃的情况下,这种方法也是有效的。

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