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中文摘要：
为了得到精密的GPS定位结果，必须对载波相位中的周跳进行有效地探测与修复．分析了周跳发生的原因及其特性，提出了一种周跳探测与修复的二步法．首先对信号进行小波多分辨率分析，根据小波系数的模极大值点的位置准确探测出周跳发生的历元；然后对周跳两侧的信号采用神经网络进行分别预测，通过对比预测值的不同来确定出周跳的大小，从而实现了周跳的修复．文末，利用实测的相位数据，验证了方法的可行性与有效性．
英文摘要：
In order to attain high precision positioning and navigation results with GPS, cycle slips must be correctly detected and repaired at the data preprocessing stage. Based on the characteristics of cycle slip we analyzed, a novel two-stage method was developed. Firstly, the wavelet multi-resolution analysis （MRA） is carried out and then the location of the cycle slip can be detected by ascertaining the point of modulus maximal value of the wavelet coefficients since the cycle slip can be regarded as the singular point of the signal. Secondly, two prediction models based on artificial neural network （ANN） are established respectively at the both side of the cycle slip. The actual number of cycle slip can be determined through comparing the difference of forecasting data of the two prediction models. Finally, test results are presented to demonstrate the feasibility and validity of the method.
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