Print Email Facebook Twitter 2D Modeling and Classification of Extended Objects in a Network of HRR Radars Title 2D Modeling and Classification of Extended Objects in a Network of HRR Radars Author Fasoula, A. Contributor Van Genderen, P. (promotor) Ligthart, L. (promotor) Faculty Electrical Engineering, Mathematics and Computer Science Department IRCTR/MTSRadar Date 2011-11-28 Abstract In this thesis, the modeling of extended objects with low-dimensional representations of their 2D geometry is addressed. The ultimate objective is the classification of the objects using libraries of such compact 2D object models that are much smaller than in the state-of-the-art classification schemes based on (High Range Resolution) HRR data. The considered input information consists of HRR datasets measured at widely separated aspect angles of the object, thus being highly sparse in the angular dimension. Such input datasets are supposedly available from a network of scanning surveillance radars. Subject radar networkhigh resolution2D object modelingradar target classificationparametric estimationsparse representation To reference this document use: http://resolver.tudelft.nl/uuid:2d6048d2-e006-4859-b3e2-24b71d7e5e97 Publisher Ipskamp Drukkers ISBN 9789461910394 Part of collection Institutional Repository Document type doctoral thesis Rights (c) 2011 Fasoula, A. Files PDF AFasoula_final_thesis_.pdf 13.3 MB Close viewer /islandora/object/uuid:2d6048d2-e006-4859-b3e2-24b71d7e5e97/datastream/OBJ/view