SAR image dataset of military ground targets with multiple poses for ATR

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dc.contributor.authorBelloni, Carole
dc.contributor.authorBalleri, Alessio
dc.contributor.authorAouf, Nabil
dc.contributor.authorMerlet, Thomas
dc.contributor.authorLe Caillec, Jean-Marc
dc.date.accessioned2019-07-26T10:51:35Z
dc.date.available2019-07-26T10:51:35Z
dc.date.issued2017-10-05
dc.description.abstractAutomatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability.Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques arecurrently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.en_UK
dc.identifier.citationBelloni C, Balleri A, Aouf N, Merlet T & Le Caillec JM (2017) SAR image dataset of military ground targets with multiple poses for ATR. In: Proceedings Volume 10432: Target and Background Signatures III, 2017, Warsaw, 11-12 September 2017.en_UK
dc.identifier.isbn978-1-5106-1328-7
dc.identifier.issn0277-786X
dc.identifier.urihttps://doi.org/10.1117/12.2277914
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/14396
dc.language.isoenen_UK
dc.publisherSPIEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectSARen_UK
dc.subjectISARen_UK
dc.subjectATRen_UK
dc.subjectDataseten_UK
dc.subjectMGTDen_UK
dc.titleSAR image dataset of military ground targets with multiple poses for ATRen_UK
dc.typeConference paperen_UK

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