一种新的GPS载波相位周跳探测与修复方法

分析了周跳产生的原因及特性,将其视为GPS载波相位测量数据的故障现象、将周跳探测等效为载波相位故障特征提取问题, 并在此基础上提出了一种新的周跳探测与修复方法。首先对载波相位测量数据进行4次差分处理;然后对差分序列进行希尔伯特-黄变换,通过变换后高频分量模极大值点的位置探测周跳;最后应用径向基函数神经网络对载波相位测量数据进行预测,通过对比预测值与实际测量值修复周跳。实际数据验证了方法的有效性与可行性。

A New Method for Cycle-Slip Detection and Correction in GPS Carrier Phase

Based on the characteristics of cycle-slip, it is regarded as the fault of GPS carrier phase observations, and then how to detect it is considered as the problem of fault feature extraction. According to these analyses, a new algorithm for detecting and correcting cycle-slip is presented. The fourth difference series of carrier phase observations are calculated. Then, the Huang-Hilbert transform is carried out to the difference series, and the location of cycle-slip can be detected by ascertaining the point of modulus maximal value of the high frequency coefficients. Finally, the forecasted model of carrier phase observations on the basis of RBF neural network is established. The number of cycle-slip can be determined by comparing the difference between the forecasted and actual values. Experimental results are presented to demonstrate the feasibility and validity of the method.