A multilinear direction finding (DF) approach for a sensor-array with multiple scales of invariance

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.

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Source https://hal.science/hal-00992223
Author Miron, Sebastian, Song, Yang, Brie, David, Wong, Kainam, Thomas
Maintainer CCSD
Last Updated May 5, 2026, 11:02 (UTC)
Created May 5, 2026, 11:02 (UTC)
Identifier hal-00992223
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Centre de Recherche en Automatique de Nancy (CRAN) ; Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
creator Miron, Sebastian
date 2013-12-20T00:00:00
harvest_object_id 68dd95b0-acf3-4c06-ad03-6bae44753d37
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-11-04T00:00:00
set_spec type:REPORT