Through-wall uwb radar based on sparse deconvolution with arctangent regularization for locating human subjects

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dc.contributor.authorRittiplang, Artit
dc.contributor.authorPhasukkit, Pattarapong
dc.date.accessioned2026-08-06T10:32:22Z
dc.date.available2026-08-06T10:32:22Z
dc.date.issued2021-04-01
dc.description.abstractA 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 ultrawideband (UWB) radar by sparse deconvolution based on arctangent regulariza-tion. Arctangent regularization is one of the suitably nonconvex regularizations that can provide a reliable solution and more accuracy, compared with convex regularizations. An iterative technique for this deconvolution problem is derived by the majorization–minimization (MM) approach so that the problem can be solved efficiently. In the various experiments, sparse deconvolution with the arctangent regularization can identify human positions from the noisy received signals of through-wall UWB radar. Although the proposed method is an odd concept, the interest of this paper is in applying sparse deconvolution, based on arctangent regularization with an S-band UWB radar, to provide a more accurate detection of a human position behind a concrete wall.
dc.identifier.citationSensors, 21(7), 2021
dc.identifier.doi10.3390/s21072488
dc.identifier.issn14248220
dc.identifier.other2-s2.0-85103491131
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/11969
dc.sourceSensors
dc.subjectArctangent regular-ization
dc.subjectMajorization–minimization (MM) algorithm
dc.subjectSparse deconvolution
dc.subjectThrough-wall radar
dc.subjectUWB radar
dc.titleThrough-wall uwb radar based on sparse deconvolution with arctangent regularization for locating human subjects
dc.typeArticle

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