Abstract:The noise level of MW combination is sometimes high, causing the possibility of miss detection when using the TurboEdit algorithm. The noise property of MW is analyzed and the actual ability of cycle slip detection is evaluated. The EMD threshold de-noising method is proposed to reduce noise level of MW. To deal with the end effect of EMD, the data to be decomposed is extended by a set of data, which is formed by adding virtual noise on the time average value of MW. The thresholds of the IMFs generated by EMD of MW are estimated and used to threshold the noise. The new characteristic of de-noised MW with cycle slip is analyzed. It is found that the cycle slip will spread to neighboring data and a detection scheme based on the de-noised MW is proposed
GAN Yu,SUI Lifen,QI Guobin et al. Improving the Performance of MW Combined Observation on Cycle Slip
Detection Using EMD Threshold De-Noising[J]. jgg, 2015, 35(4): 666-670.