Non-supervised Machine Learning Algorithms for Radar Clutter High-Resolution Doppler Segmentation and Pathological Clutter Analysis
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en
Communication dans un congrès
Ce document a été publié dans
2019 20th International Radar Symposium (IRS), 2019 20th International Radar Symposium (IRS), International Radar Symposium, 2019-06-26, Ulm.
Résumé en anglais
Here we propose a method to classify radar clutter from radar data using a non-supervised classification algorithm. Thus new radars will be able to use the experience of other radars, which will improve their performance: ...Lire la suite >
Here we propose a method to classify radar clutter from radar data using a non-supervised classification algorithm. Thus new radars will be able to use the experience of other radars, which will improve their performance: learning pathological radar clutter can be used to fix some false alarm rate created by strong echoes coming from hail, rain, waves, mountains, cities; it will also improve the detectability of slow moving targets, like drones, which can be hidden in the clutter, flying close to the landform.< Réduire
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