Non-Supervised High Resolution Doppler Machine Learning for Pathological Radar Clutter
Langue
en
Communication dans un congrès
Ce document a été publié dans
2019 International Radar Conference (RADAR), 2019 International Radar Conference (RADAR), RADAR 2019, 2020-09-23, Toulon.
Résumé en anglais
In this paper we propose a method to classify radar clutter from radar data using a non-supervised classification algorithm. As a final objective, new radars will therefore be able to use the experience of other radars to ...Lire la suite >
In this paper we propose a method to classify radar clutter from radar data using a non-supervised classification algorithm. As a final objective, new radars will therefore be able to use the experience of other radars to improve their performances: 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
Mots clés en anglais
non-supervised classification
machine learning
radar clutter
k-means
autocorrelation matrix
Burg algorithm
reflection coefficients
Kähler metric
Origine
Importé de halUnités de recherche