CANDECOMP/PARAFAC (CP) direction finding with multi-scale array

Sebastian Miron; Yang Song; David Brie; Kainam Thomas Wong

doi:10.1109/CAMSAP.2013.6714048

CANDECOMP/PARAFAC (CP) direction finding with multi-scale array

Sebastian Miron, Yang Song, David Brie, Kainam Thomas Wong

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

In this paper, we introduce a novel direction of arrival (DOA) estimation algorithm for an array presenting multiple scales of invariance, based on a CANDECOMP/PARAFAC (CP) model of the data. The proposed approach is a generalization of the results given in [1] to an array presenting an arbitrary number of spatial invariances. We show, on a particular array geometry, that our method could out-perform the ESPRIT-based approach introduced in [2].

Original language	English
Title of host publication	2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
Pages	224-227
Number of pages	4
DOIs	https://doi.org/10.1109/CAMSAP.2013.6714048
Publication status	Published - 1 Dec 2013
Event	2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013 - Saint Martin, France Duration: 15 Dec 2013 → 18 Dec 2013

Conference

Conference	2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
Country/Territory	France
City	Saint Martin
Period	15/12/13 → 18/12/13

ASJC Scopus subject areas

Computer Science Applications

More information

10.1109/CAMSAP.2013.6714048

Cite this

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title = "CANDECOMP/PARAFAC (CP) direction finding with multi-scale array",

abstract = "In this paper, we introduce a novel direction of arrival (DOA) estimation algorithm for an array presenting multiple scales of invariance, based on a CANDECOMP/PARAFAC (CP) model of the data. The proposed approach is a generalization of the results given in [1] to an array presenting an arbitrary number of spatial invariances. We show, on a particular array geometry, that our method could out-perform the ESPRIT-based approach introduced in [2].",

author = "Sebastian Miron and Yang Song and David Brie and Wong, {Kainam Thomas}",

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Miron, S, Song, Y, Brie, D & Wong, KT 2013, CANDECOMP/PARAFAC (CP) direction finding with multi-scale array. in 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013., 6714048, pp. 224-227, 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013, Saint Martin, France, 15/12/13. https://doi.org/10.1109/CAMSAP.2013.6714048

CANDECOMP/PARAFAC (CP) direction finding with multi-scale array. / Miron, Sebastian; Song, Yang; Brie, David et al.

2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013. 2013. p. 224-227 6714048.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - In this paper, we introduce a novel direction of arrival (DOA) estimation algorithm for an array presenting multiple scales of invariance, based on a CANDECOMP/PARAFAC (CP) model of the data. The proposed approach is a generalization of the results given in [1] to an array presenting an arbitrary number of spatial invariances. We show, on a particular array geometry, that our method could out-perform the ESPRIT-based approach introduced in [2].

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CANDECOMP/PARAFAC (CP) direction finding with multi-scale array

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