The InflateSAR Campaign: Testing SAR Vessel Detection Systems for Refugee Rubber Inflatables

Remote Sensing

Armando Marino¹  Peter Lanz²  Matthias Möller³  Frank Köster⁴  Thomas Brinkhoff⁵ 

[1] Department of Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA, UK;Department of Computing Science, Carl von Ossietzky University of Oldenburg, Ammerländer Heerstraße 114-118, 26129 Oldenburg, Germany;Faculty for Humanities and Cultural Sciences, Otto-Friedrich-University of Bamberg, Am Kranen, 96045 Bamberg, Germany;Institute for AI Safety and Security, German Aerospace Center (DLR), Rathausallee 12, 53757 Sankt Augustin, Germany;Institute for Applied Photogrammetry and Geoinformatics, Jade University Oldenburg, Ofener Str. 16/19, 26121 Oldenburg, Germany;

关键词: constant false alarm rate (CFAR) detector;    polarimetric detector;    sub-look detector;    vessel detection systems;    ship detection;    synthetic aperture radar (SAR);   

DOI  :  10.3390/rs13081487

来源: DOAJ

【 摘 要 】

Countless numbers of people lost their lives at Europe’s southern borders in recent years in the attempt to cross to Europe in small rubber inflatables. This work examines satellite-based approaches to build up future systems that can automatically detect those boats. We compare the performance of several automatic vessel detectors using real synthetic aperture radar (SAR) data from X-band and C-band sensors on TerraSAR-X and Sentinel-1. The data was collected in an experimental campaign where an empty boat lies on a lake’s surface to analyse the influence of main sensor parameters (incidence angle, polarization mode, spatial resolution) on the detectability of our inflatable. All detectors are implemented with a moving window and use local clutter statistics from the adjacent water surface. Among tested detectors are well-known intensity-based (CA-CFAR), sublook-based (sublook correlation) and polarimetric-based (PWF, PMF, PNF, entropy, symmetry and iDPolRAD) approaches. Additionally, we introduced a new version of the volume detecting iDPolRAD aimed at detecting surface anomalies and compare two approaches to combine the volume and the surface in one algorithm, producing two new highly performing detectors. The results are compared with receiver operating characteristic (ROC) curves, enabling us to compare detectors independently of threshold selection.

【 授权许可】

Unknown