A multilinear direction finding (DF) approach for a sensor-array with multiple scales of invariance
type: Distribution
access URL: https://hal.science/hal-00992223
format: HTML
issued: 2026-05-05T11:02:12.913945
modified: 2026-05-05T11:02:12.894636

test_moissonnage_selune
type: Agent

A multilinear direction finding (DF) approach for a sensor-array with multiple scales of invariance
type: Dataset
contact point: Organization
  fn: CCSD
keyword: reports
keyword: candecompparafac-decomposition
keyword: doa-estimation
keyword: multi-scale-array
keyword: spisignalengineering-sciences-physicssignal-and-image-processing
keyword: infoinfo-tscomputer-science-cssignal-and-image-processing
keyword: infoeu-reposemanticsreport
keyword: direction-finding
landing page: https://hal.science/hal-00992223
description: In this paper, we introduce a novel direction finding algorithm for a multi-scale sensor-array, that is, an array presenting multiple scales of invariance. We show that the collected data can be represented as a Candecomp/Parafac (CP) model, for which we analyze the identifiability properties. A two-stage algorithm for direction-of-arrival (DOA) estimation with such an array is also proposed. This approach generalizes the results given in [Sidiropoulos et al., 2000] to an array that presents an arbitrary number of spatial invariances. We illustrate, on a particular array geometry, that our method outperforms the ESPRIT-based approach introduced in [Wong and Zoltowski, 1998]. Moreover, we show that the single-snapshot case can be handled by our method, provided that the array includes at least three scale-levels.
issued: 2026-05-05T11:02:12.907377
language: en
modified: 2026-05-05T11:02:12.907381