Abstract
In this paper, a wire detection algorithm is proposed for synthetic aperture radar (SAR) images. The algorithm is specifically designed for SAR images generated from an agile, drone-mounted, omnidirectional radar array to be used for the detection of improvised explosive devices (IEDs). A multistage approach consisting of denoising, constant false alarm rate (CFAR) thresholding, feature extraction, and automated detection using the Radon transform, is proposed and applied to a set of SAR images with multiple aspect angles. At each detection step, the look-angles of individual pixels are used to remove false alarms, and improve detection accuracy. The algorithm is tested using measured data and provides an acceptable detection performance on straight wire segments even in the presence of a strong background clutter.
Original language | English |
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Title of host publication | 2020 IEEE Radar Conference, RadarConf 2020 |
Publisher | IEEE |
Pages | 1559-1564 |
Number of pages | 6 |
ISBN (Electronic) | 9781728189420 |
DOIs | |
Publication status | Published - Sept 2020 |
Event | 17th European Radar Conference: in the framework of the European Microwave Week 2020 - Utrecht, Netherlands Duration: 16 Sept 2020 → 18 Sept 2020 https://www.eumweek.com/conferences/eurad.html |
Publication series
Name | IEEE National Radar Conference - Proceedings |
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Volume | 2020-September |
ISSN (Print) | 1097-5659 |
Conference
Conference | 17th European Radar Conference: in the framework of the European Microwave Week 2020 |
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Abbreviated title | EuRAD-2020 |
Country/Territory | Netherlands |
City | Utrecht |
Period | 16/09/20 → 18/09/20 |
Internet address |