ZHU GuangBin,
CHANG XiaoTao,
FU XingKe et al
.2018.A method for constructing the optimal ARMA filtering model on the satellite gravity gradiometry data Chinese Journal of Geophysics(in Chinese),61(12): 4729-4736,doi: 10.6038/cjg2018M0040
A method for constructing the optimal ARMA filtering model on the satellite gravity gradiometry data
ZHU GuangBin1, CHANG XiaoTao1,2, FU XingKe1, QU QingLiang1,2
1. Satellite Surveying and Mapping Application Center, NASG, Beijing 100048, China; 2. College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
Abstract：Due to the colored noise in the massive satellite gravity gradiometry observations, when determining the least square solution of the gravity field model using the direct method, the covariance matrix of the observations is a huge non-diagonal matrix, which brings great difficulties to numerical computation. To solve this problem, this work proposes a method of constructing the optimal ARMA filtering model based on the prior error power spectrum density, which realizes the efficient filtering of satellite gravity gradiometry observations combined with the block solving strategy. The numerical simulation analyses show that after the processing in the time domain with the optimal ARMA filter, the state of the normal equation matrix is improved obviously, and the colored noises mixed into the gravity gradiometry measurements are whitened efficiently, while the accuracy of the geoid increases significantly.
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