Sparsity-based methods have recently come to the foreground of damage detection applications posing a robust and efficient alternative for traditional approaches. At the same time, low-frequency inspection is known to enable global monitoring with waves propagating over large distances. In this paper, a single sensor complex Group Lasso methodology for the problem of structural defect localization by means of compressive sensing and complex low-frequency response functions is presented. The complex Group Lasso methodology is evaluated on composite plates with induced scatterers. An adaptive setting of the methodology is also proposed to further enhance resolution. Results from both approaches are compared with a full-array, super-resolution MUSIC technique of the same signal model. Both algorithms are shown to demonstrate high and competitive performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.