Denoising of GNSS Station Coordinate Time Series Based on PSO-VMD-SSA
Influenced by equipment,environment,and other factors,the GNSS(Global Navigation Satellite System)inevitably col-lects coordinate data with noise interference.Traditional variational mode decomposition(VMD)decomposes the original signal into components with different center frequencies and realizes noise suppression based on the characteristics of signal components and noise components.However,on the one hand,this denoising method has the problem of subjectivity in parameter selection,on the other hand,it has the problem of eliminating the useful information in the noise component.Based on this,this paper introduces Particle Swarm Optimization(PSO)algorithm and Singular Spectrum Analysis(SSA)method on the basis of VMD method to build a new PSO-VMD-SSA combined denoising method.The denoising experiment using the measured GNSS station coordinate time series shows that the proposed method has significantly improved the denoising effect compared with VMD method and SSA method,which verifies the effectiveness and superiority of the proposed method.
variational mode decompositionparticle swarm optimization algorithmsingular spectrum analysistime series denoising
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