A method of statistical modelling for gravity field based on spectral analysis
Statistical characteristics for the gravity field mainly include covariance(correlation),power spectral density and degree variance,which form the base of characterizing the gravity field from the spatial domain,frequency domain and spherical harmonic domain.In this paper,we present a self-consistent and analytic method to modelling the gravitational statistic using power spectral derived from the reciprocal distance covariance of the disturbing potential.Three sets of model parameters were obtained by fitting to power spectra of high-resolution ground gravity anomaly and airborne gravity gradient data combined with EGM2008,respectively.To study the feasibility of the method,our model was numerically compared with classical ones in terms of power spectra and degree variance,and we find that our model furthermore ensures a good fit to actual power spectra at various scales.The model was also tested on simulation of high-frequency gravity field.We concluded that the closed form of our covariance and spectral density functions are particularly useful for quantitative analysis of gravity gradient detection,random simulation of high frequency gravity field and gravity field collocation.Also,a more precise model can be yielded by our methods with available data sets.
Power spectral densityCovarianceDegree variancesStatistical characterAirborne gravity gradientThe reciprocal distance model
万方数据
维普
