GNSS Coordinate Time Series Gross Error Detection And Noise Estimation Research

With the development of science and technology,GNSS technology plays a more and more important role in today’s society,at the same time GNSS reference station coordinate data of continuous observation for many years,it provides a data basis to the research of GNSS time series,and GNSS time series contains abundant geophysical information,so the GNSS coordinates,precise analysis of time series,It is of great significance to geophysical research,climate and meteorology forecast,crustal deformation in the region and so on.Because of the GNSS signals from generation,transmission,to be in the process of the receiver to receive will be under the influence of various error sources,makes the GNSS inevitably contains gross error in the signal and noise,the existence of gross error will have negative impact on data analysis and noise processing,so before for data analysis and noise processing requires gross error detection and eliminate;The noise in GNSS coordinate time series contains not only white noise but also colored noise,which makes the noise more complex.Therefore,there are two ways to deal with noise.The first way is to remove noise and extract useful signals in the data,and reduce the influence of noise through correlation analysis of extracted signals.The second one estimates the amplitude of noise to build a suitable noise model,and then uses the adjustment method to calculate the value of the parameters.In view of this,this paper focuses on GNSS coordinate time series gross error detection,noise elimination to extract effective signals,and variance-covariance component estimation method of noise model estimation,the main work of this paper is as follows:(1)The principle of GNSS coordinate time series is systematically introduced,and the existing model of GNSS coordinate time series is emphatically analyzed.Then,the noise types contained in GNSS coordinate time series and the composition of GNSS coordinate time series random model are introduced,which provides a theoretical basis for the subsequent research.(2)In view of the problem that time series inevitably are affected by various error sources and the signal contains gross error,a gross error detection method combining singular spectrum analysis(SSA)and S_n estimator is proposed.Singular spectrum analysis decomposes time series signals into trend term,periodic term and residual term.Then,S_n estimators are used to detect the gross errors of the residual term,so as to avoid the influence of trend lines and periodic term on gross errors detection.Experiments are carried out through simulation data and measured data,and the results show that the SSA-SN algorithm is more accurate than the traditional method for gross errors detection,and has better sensitivity to outliers.(3)Aiming at the problem that GNSS coordinate time series noise is difficult to be effectively filtered,which affects the accuracy and results of data analysis,an improved denoising method combining variational mode decomposition and wavelet packet analysis is proposed.The method takes energy entropy mutual information(EEMI),which is composed of energy entropy and mutual information,as an indicator.Before the sum of two mode EEMI modal function as objective function,optimize the VMD parameters,using the algorithm of GOA so as to solve the problem of VMD parameters need to be set in advance,then USES the method of optimization to get the optimal parameter combination into VMD in time series signal extraction,the isolated noise using wavelet packet analysis to further signal extraction,Finally,the two extracted signals are reconstructed into new signals,and the effectiveness and feasibility of the method are verified by two simulation examples and two measured data.(4)In order to solve the precise and efficient problem of GNSS coordinate time series noise component,combining the equivalent conditional adjustment model and the minimum norm quadratic unbiased estimation method,the estimation method of the minimum norm component of equivalent conditional closure error is proposed.Minque-ecm(Minimum Norm QUADRATIC Unbiased Estimation Based on the Equivalent Condition Misclosure).Firstly,the quadratic variance estimation formula is constructed by using equivalent conditional closure error.Combining invariance,unbiasedness and minimum norm criterion,the minimum norm estimation formula of variance-covariance component based on equivalent conditional closure error is derived.And then,Ls-vce(least-squares variance Component Estimation)and MINQUE(Minimum Norm QUADRATIC Unbiased)were adopted Estimate method verifies the correctness of the proposed method and the validity of the algorithm.The noise estimation results of the simulated time series and the coordinate time series of GNSS stations in North America show that the proposed method is consistent with the ESTIMATION results of LS-VCE and MINQUE methods,but the calculation time is 20% higher than that of LS-VCE.