Echo Signal Extraction Based on Improved Singular Spectrum Analysis and Compressed Sensing in Wavelet Domain

Abstract

A novel framework of signal extraction is proposed based on improved singular spectrum analysis (SSA) and compressed sensing (CS) for laser radar. The improved signal selection method, which locates a cutoff point on the singular spectrum curve, is fused into the SSA to reduce the noise. Afterward, the CS in the wavelet domain is employed to acquire the observation vector, and the improved reconstruction algorithm with a hard threshold denoising method reduces the noise furthermore. The simulations and experiments are performed to verify the superiority of the proposed algorithm compared with other algorithms. The proposed algorithm can enhance a signal-to-noise ratio while reducing the distortion of the received signal.

Abnormal State Detection of OLTC Based on Improved Fuzzy C-means Clustering

“…Thereafter, the signal denoised by WP is subjected to the secondary denoising using SSA. Generally, the SSA is used to remove small noise disturbances in the signal [20][21] . While maintaining the signal characteristics as far as possible, it improves the denoising accuracy and meets the requirements of secondary denoising.…”