Through-Wall UWB Radar Based on Sparse Deconvolution with Arctangent Regularization for Locating Human Subjects

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 7; p. 2488
• Main Authors: Rittiplang, Artit, Phasukkit, Pattarapong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 03.04.2021; MDPI
• Subjects: Algorithms; arctangent regularization; Human subjects; Humans; majorization–minimization (MM) algorithm; Noise; Numerical analysis; Optimization; Radar; Research Design; Research Subjects; Respiration; sparse deconvolution; Sparsity; through-wall radar; UWB radar; through-wall radar; majorization–minimization (MM) algorithm; arctangent regularization; sparse deconvolution; UWB radar

A common problem in through-wall radar is reflected signals much attenuated by wall and environmental noise. The reflected signal is a convolution product of a wavelet and an unknown object time series. This paper aims to extract the object time series from a noisy receiving signal of through-wall u...