Sparsity based TomoSAR combining CS and GLRT
Conference: EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar
06/04/2018 - 06/07/2018 at Aachen, Germany
Proceedings: EUSAR 2018
Pages: 4Language: englishTyp: PDFPersonal VDE Members are entitled to a 10% discount on this title
Budillon, Alessandra; Johnsy, Angel Caroline; Schirinzi, Gilda (University of Naples Parthenope, Italy)
In this paper a new approach to TomoSAR imaging is presented. It is based on the joint use of a Constant False Alarm Rate (CFAR) detection approach of multiple targets and of Compressive Sampling (CS) tomographic reconstructions. CS is widely used to recover a sparse signal but suffers from the presence of outliers. The proposed method consists in applying a Generalized Likelihood Ratio Test (GLRT) exploiting the CS reconstruction in order to detect and accurately localize single and double scatterers with a given false alarm probability, avoiding outliers and artefacts.