Random matrix theory applied to low rank stap detection
type: Dataset
description: International audience
issued: 2026-05-09T10:38:01.277355
language: en
modified: 2026-05-09T10:38:01.277359
contact point: Organization
  fn: CCSD
keyword: adaptive-normalized-matched-filter
keyword: conference-papers
keyword: g-music-estimator
keyword: infoeu-reposemanticsconferenceobject
keyword: infoinfo-tscomputer-science-cssignal-and-image-processing
keyword: low-rank-detection
keyword: random-matrix-theory
keyword: spisignalengineering-sciences-physicssignal-and-image-processing
keyword: stap-processing
landing page: 21st European Signal Processing Conference (EUSIPCO 2013)

Random matrix theory applied to low rank stap detection
type: Distribution
format: HTML
issued: 2026-05-09T10:38:01.293857
modified: 2026-05-09T10:38:01.264313
access URL: https://hal.science/hal-00871217

test_moissonnage_selune
type: Agent