Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays

Tom Tirer; Oded Bialer

doi:10.1109/icassp40776.2020.9053204

Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays

Tom Tirer, Oded Bialer

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

We consider the problem of estimating the angles of arrival (AOAs) of multiple sources from a single snapshot obtained by a set of non-coherent sub-arrays, i.e., while the antenna elements in each sub-array are coherent, each sub-array observes a different unknown phase. Previous relevant works are based on eigendecomposition of the sample covariance, which requires a large number of snapshots, or on combining the sub-arrays using non-coherent processing methods. In this paper, we propose a technique to estimate the sub-arrays phase offsets for a given AOAs hypothesis, which facilitates approximate maximum likelihood estimation of the AOAs from a single snapshot. Numerical experiments show that the proposed approach clearly outperforms non-coherent processing, and even attains the Cramér-Rao lower bound in various scenarios.

Original language	English
Title of host publication	2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4557-4561
Number of pages	5
ISBN (Electronic)	9781509066315
DOIs	https://doi.org/10.1109/icassp40776.2020.9053204
State	Published - May 2020
Externally published	Yes
Event	2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain Duration: 4 May 2020 → 8 May 2020

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2020-May
ISSN (Print)	1520-6149

Conference

Conference	2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Country/Territory	Spain
City	Barcelona
Period	4/05/20 → 8/05/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

Angle of arrival
array processing
maximum likelihood estimation
multiple sources
single snapshot.

Access to Document

10.1109/icassp40776.2020.9053204

Cite this

Tirer, T., & Bialer, O. (2020). Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays. In 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings (pp. 4557-4561). Article 9053204 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2020-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icassp40776.2020.9053204

Tirer, Tom ; Bialer, Oded. / Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays. 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 4557-4561 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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abstract = "We consider the problem of estimating the angles of arrival (AOAs) of multiple sources from a single snapshot obtained by a set of non-coherent sub-arrays, i.e., while the antenna elements in each sub-array are coherent, each sub-array observes a different unknown phase. Previous relevant works are based on eigendecomposition of the sample covariance, which requires a large number of snapshots, or on combining the sub-arrays using non-coherent processing methods. In this paper, we propose a technique to estimate the sub-arrays phase offsets for a given AOAs hypothesis, which facilitates approximate maximum likelihood estimation of the AOAs from a single snapshot. Numerical experiments show that the proposed approach clearly outperforms non-coherent processing, and even attains the Cram{\'e}r-Rao lower bound in various scenarios.",

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Tirer, T & Bialer, O 2020, Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays. in 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings., 9053204, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2020-May, Institute of Electrical and Electronics Engineers Inc., pp. 4557-4561, 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, Barcelona, Spain, 4/05/20. https://doi.org/10.1109/icassp40776.2020.9053204

Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays. / Tirer, Tom; Bialer, Oded.
2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 4557-4561 9053204 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2020-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - We consider the problem of estimating the angles of arrival (AOAs) of multiple sources from a single snapshot obtained by a set of non-coherent sub-arrays, i.e., while the antenna elements in each sub-array are coherent, each sub-array observes a different unknown phase. Previous relevant works are based on eigendecomposition of the sample covariance, which requires a large number of snapshots, or on combining the sub-arrays using non-coherent processing methods. In this paper, we propose a technique to estimate the sub-arrays phase offsets for a given AOAs hypothesis, which facilitates approximate maximum likelihood estimation of the AOAs from a single snapshot. Numerical experiments show that the proposed approach clearly outperforms non-coherent processing, and even attains the Cramér-Rao lower bound in various scenarios.

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Tirer T, Bialer O. Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays. In 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 4557-4561. 9053204. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/icassp40776.2020.9053204

Effective Approximate Maximum Likelihood Estimation of Angles of Arrival for Non-Coherent Sub-Arrays

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Keywords

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