OUTLIER DETECTION ALGORITHM FOR SATELLITE GRAVITY GRADIENT DATA BY USING WAVELET SHRINKAGE DENOISING
Wu Yunlong 1) ; Luo Zhicai 1, 2) ; Li Hui 3) ; and Zhong Bo 1)
1)School of Geodesy and Geomatics, Wuhan University, Wuhan 4300792)Key Lab. of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, Wuhan 4300793)Institute of Seismology, CEA, Wuhan 430071
Abstract��On the basis of wavelet theory, the outlier detection algorithm in satellite gravity gradiometry using wavelet shrinkage denoising is established, and simulation data with white noise and outliers is generated. The computed and analysis results indicate that wavelet method is a novel outlier detection algorithm with 97% ratio of success.
Wu Yunlong ,Luo Zhicai,Li Hui et al. OUTLIER DETECTION ALGORITHM FOR SATELLITE GRAVITY GRADIENT DATA BY USING WAVELET SHRINKAGE DENOISING[J]. jgg, 2010, 30(4): 55-58.
