A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition

Atmospheric lidar is susceptible to the influence of light attenuation, sky background light, and detector dark currents during detection process. This results in a large amount noise return signal. To reduce extract useful signal, novel denoising method combined with variational modal decomposition (VMD), sparrow search algorithm (SSA) singular value (SVD) proposed. The SSA used optimize number layers K quadratic penalty factor ? values VMD algorithm. Some intrinsic mode function (IMF) components obtained from VMD-SSA are grouped reconstructed according interrelationship selection criterion. Then, signal further denoised by combining strong noise-reduction ability SVD obtain clean verify effectiveness VMD-SSA-SVD method, compared analysed wavelet packet decomposition, empirical (EMD), ensemble (EEMD), adaptive noise-complete (CEEMD), its effect considerably improved over that other four methods. can eliminate complex while retaining all details not distorted, waveform smoother, far-field interference be suppressed. closer real higher accuracy, which shows feasibility practicality proposed method.