Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound

Costas A. Kokke; Mario Coutino; Laura Anitori; Richard Heusdens; Geert Leus

doi:10.1109/ICASSP49357.2023.10094942

Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound

Costas A. Kokke, Mario Coutino, Laura Anitori, Richard Heusdens, Geert Leus

Signal Processing Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

13 Downloads (Pure)

Abstract

Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we propose to tackle the sensor selection problem for angle of arrival estimation using the worst-case Cramér-Rao bound of two uncorrelated sources. To do so, we cast the problem as a convex semi-definite program and retrieve the binary selection by randomized rounding. Through numerical examples related to a linear array, we illustrate the proposed method and show that it leads to the natural selection of elements at the edges plus the center of the linear array. This contrasts with the typical solutions obtained from minimizing the single-target Cramér-Rao bound.

Original language	English
Title of host publication	Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Place of Publication	Piscataway
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	978-1-7281-6327-7
ISBN (Print)	978-1-7281-6328-4
DOIs	https://doi.org/10.1109/ICASSP49357.2023.10094942
Publication status	Published - 2023
Event	48th IEEE International Conference on Acoustics, Speech and Signal Processing 2023 - Rhodes Island, Greece Duration: 4 Jun 2023 → 10 Jun 2023

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2023-June
ISSN (Print)	1520-6149

Conference

Conference	48th IEEE International Conference on Acoustics, Speech and Signal Processing 2023
Abbreviated title	ICASSP 2023
Country/Territory	Greece
City	Rhodes Island
Period	4/06/23 → 10/06/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

sparse sensing
cramér-rao bound
multi-target estimation
array processing
sensor selection

Access to Document

10.1109/ICASSP49357.2023.10094942

Sensor_Selection_for_Angle_of_Arrival_Estimation_Based_on_the_Two-Target_Cramr-Rao_BoundFinal published version, 984 KB

Cite this

Kokke, C. A., Coutino, M., Anitori, L., Heusdens, R., & Leus, G. (2023). Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound. In Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2023-June). IEEE. https://doi.org/10.1109/ICASSP49357.2023.10094942

Kokke, Costas A. ; Coutino, Mario ; Anitori, Laura et al. / Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound. Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Piscataway : IEEE, 2023. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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title = "Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cram{\'e}r-Rao Bound",

abstract = "Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cram{\'e}r-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we propose to tackle the sensor selection problem for angle of arrival estimation using the worst-case Cram{\'e}r-Rao bound of two uncorrelated sources. To do so, we cast the problem as a convex semi-definite program and retrieve the binary selection by randomized rounding. Through numerical examples related to a linear array, we illustrate the proposed method and show that it leads to the natural selection of elements at the edges plus the center of the linear array. This contrasts with the typical solutions obtained from minimizing the single-target Cram{\'e}r-Rao bound.",

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author = "Kokke, {Costas A.} and Mario Coutino and Laura Anitori and Richard Heusdens and Geert Leus",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 48th IEEE International Conference on Acoustics, Speech and Signal Processing 2023, ICASSP 2023 ; Conference date: 04-06-2023 Through 10-06-2023",

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Kokke, CA, Coutino, M, Anitori, L, Heusdens, R & Leus, G 2023, Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound. in Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2023-June, IEEE, Piscataway, 48th IEEE International Conference on Acoustics, Speech and Signal Processing 2023, Rhodes Island, Greece, 4/06/23. https://doi.org/10.1109/ICASSP49357.2023.10094942

Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound. / Kokke, Costas A.; Coutino, Mario; Anitori, Laura et al.
Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Piscataway: IEEE, 2023. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2023-June).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Coutino, Mario

AU - Anitori, Laura

AU - Heusdens, Richard

AU - Leus, Geert

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2023

Y1 - 2023

N2 - Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we propose to tackle the sensor selection problem for angle of arrival estimation using the worst-case Cramér-Rao bound of two uncorrelated sources. To do so, we cast the problem as a convex semi-definite program and retrieve the binary selection by randomized rounding. Through numerical examples related to a linear array, we illustrate the proposed method and show that it leads to the natural selection of elements at the edges plus the center of the linear array. This contrasts with the typical solutions obtained from minimizing the single-target Cramér-Rao bound.

AB - Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we propose to tackle the sensor selection problem for angle of arrival estimation using the worst-case Cramér-Rao bound of two uncorrelated sources. To do so, we cast the problem as a convex semi-definite program and retrieve the binary selection by randomized rounding. Through numerical examples related to a linear array, we illustrate the proposed method and show that it leads to the natural selection of elements at the edges plus the center of the linear array. This contrasts with the typical solutions obtained from minimizing the single-target Cramér-Rao bound.

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BT - Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Kokke CA, Coutino M, Anitori L, Heusdens R , Leus G. Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound. In Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Piscataway: IEEE. 2023. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP49357.2023.10094942

Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound

Abstract

Publication series

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Bibliographical note

Keywords

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