摘要
Although the empirical mode decomposition （EMD） method is an effective tool for noise reduction in lidar signals, evaluating the effectiveness of the denoising method is difficult. A dual-field-of-view lidar for observing atmospheric aerosols is described. The backscattering signals obtained from two channels have different signal-to-noise ratios （SNRs）. The performance of noise reduction can be investigated by comparing the high SNR signal and the denoised low SNR signal without a simulation experiment. With this approach, the signal and noise are extracted to one intrinsic mode function （IMF） by the EMD- based denoising; thus, the threshold method is applied to the IMFs. Experimental results show that the improved threshold method can effectively perform noise reduction while preserving useful sudden-change information.
Although the empirical mode decomposition （EMD） method is an effective tool for noise reduction in lidar signals, evaluating the effectiveness of the denoising method is difficult. A dual-field-of-view lidar for observing atmospheric aerosols is described. The backscattering signals obtained from two channels have different signal-to-noise ratios （SNRs）. The performance of noise reduction can be investigated by comparing the high SNR signal and the denoised low SNR signal without a simulation experiment. With this approach, the signal and noise are extracted to one intrinsic mode function （IMF） by the EMD- based denoising; thus, the threshold method is applied to the IMFs. Experimental results show that the improved threshold method can effectively perform noise reduction while preserving useful sudden-change information.
基金
supported by the National "973" Program of China (Nos. 2009CB723905 and 2011CB707106)
the National Natural Science Foundation of China(Nos. 10978003 and 40871171)
