Non-supervised Machine Learning Algorithms for Radar Clutter High-Resolution Doppler Segmentation and Pathological Clutter Analysis
Language
en
Communication dans un congrès
This item was published in
2019 20th International Radar Symposium (IRS), 2019 20th International Radar Symposium (IRS), International Radar Symposium, 2019-06-26, Ulm.
English Abstract
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: ...Read more >
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.Read less <
Origin
Hal imported