An Adaptive Indicator Optimization Ensemble Empirical Mode Decomposition Method and Its Application on the Denoising of BeiDou B1I Signal

The ensemble empirical mode decomposition (EEMD) is an effective method for processing nonlinear and nonsmooth signals, solving the problem of modal mixing during the signal decomposition process. However, the selection of intrinsic mode functions (IMF) components during the EEMD reconstructed process is blindness. The IMF components are the signal components of each layer obtained after the original signal decomposed by EMD. This paper proposes an adaptive indicator optimization EEMD (AIO-EEMD) signal denoising method. Firstly, a new adaptive reconstruction component indicator r and its corresponding method are proposed by combining the traditional measurement indexes. Then, the proposed method is used to reconstruct the BeiDou signal. Finally, four different methods are used to compare the signal reconstruction experiments. The experimental results show that the proposed method is superior to the other three traditional methods and can perform better during its reconstruction process.