Echo-Signal De-Noising of CO2-DIAL Based on the Ensemble Empirical Mode Decomposition

The carbon dioxide (CO2) differential absorption lidar echo signal is susceptible to noise and must satisfy the high demand for signal-retrieval precision. Thus, a proper de-noising method should be selected improve inversion result. In this paper, we simultaneously decompose three pairs into different intrinsic mode functions (IMFs) using of ensemble empirical decomposition (EEMD). Further, correlation coefficients IMFs with same temporal scale are regarded as criterion determine components that need removal. This not only retains useful information effectively but also removes component. A significant improvement in R2 optical depth (DAOD) de-noised signals obtained. results simulated observed analysis demonstrated both SNR retrieval