Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements

Bernd Hofmann; Thomas F. Eibert

doi:10.1109/APUSNCURSINRSM.2019.8888614

Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements

Bernd Hofmann, Thomas F. Eibert

Chair of High-Frequency Engineering

Technical University of Munich

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

4 Scopus citations

Abstract

The influence of noise on the minimum number of measurement samples for a sparse recovery in a spherical antenna near-field to far-field transformation (NFFFT) is investigated. To this end, several modified phase transition diagrams are determined. These diagrams show the minimum number of samples required to achieve a certain accuracy in the reconstructed far-field. With this approach, the reconstruction by the basis pursuit algorithm and its quadratically constrained version are shown to be sufficiently robust against measurement noise for actual measurements. In consequence, sparse recovery can be applied to the spherical NFFFT with predictable accuracy.

Original language	English
Title of host publication	2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1857-1858
Number of pages	2
ISBN (Electronic)	9781728106922
DOIs	https://doi.org/10.1109/APUSNCURSINRSM.2019.8888614
State	Published - Jul 2019
Event	2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Atlanta, United States Duration: 7 Jul 2019 → 12 Jul 2019

Publication series

Name	2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings

Conference

Conference	2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019
Country/Territory	United States
City	Atlanta
Period	7/07/19 → 12/07/19

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10.1109/APUSNCURSINRSM.2019.8888614

Cite this

Hofmann, B., & Eibert, T. F. (2019). Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements. In 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings (pp. 1857-1858). Article 8888614 (2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APUSNCURSINRSM.2019.8888614

Hofmann, Bernd ; Eibert, Thomas F. / Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements. 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1857-1858 (2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings).

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title = "Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements",

abstract = "The influence of noise on the minimum number of measurement samples for a sparse recovery in a spherical antenna near-field to far-field transformation (NFFFT) is investigated. To this end, several modified phase transition diagrams are determined. These diagrams show the minimum number of samples required to achieve a certain accuracy in the reconstructed far-field. With this approach, the reconstruction by the basis pursuit algorithm and its quadratically constrained version are shown to be sufficiently robust against measurement noise for actual measurements. In consequence, sparse recovery can be applied to the spherical NFFFT with predictable accuracy.",

author = "Bernd Hofmann and Eibert, {Thomas F.}",

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language = "English",

series = "2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings",

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Hofmann, B & Eibert, TF 2019, Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements. in 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings., 8888614, 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1857-1858, 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019, Atlanta, United States, 7/07/19. https://doi.org/10.1109/APUSNCURSINRSM.2019.8888614

Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements. / Hofmann, Bernd; Eibert, Thomas F.
2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1857-1858 8888614 (2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings).

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

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N2 - The influence of noise on the minimum number of measurement samples for a sparse recovery in a spherical antenna near-field to far-field transformation (NFFFT) is investigated. To this end, several modified phase transition diagrams are determined. These diagrams show the minimum number of samples required to achieve a certain accuracy in the reconstructed far-field. With this approach, the reconstruction by the basis pursuit algorithm and its quadratically constrained version are shown to be sufficiently robust against measurement noise for actual measurements. In consequence, sparse recovery can be applied to the spherical NFFFT with predictable accuracy.

AB - The influence of noise on the minimum number of measurement samples for a sparse recovery in a spherical antenna near-field to far-field transformation (NFFFT) is investigated. To this end, several modified phase transition diagrams are determined. These diagrams show the minimum number of samples required to achieve a certain accuracy in the reconstructed far-field. With this approach, the reconstruction by the basis pursuit algorithm and its quadratically constrained version are shown to be sufficiently robust against measurement noise for actual measurements. In consequence, sparse recovery can be applied to the spherical NFFFT with predictable accuracy.

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Hofmann B, Eibert TF. Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements. In 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1857-1858. 8888614. (2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings). doi: 10.1109/APUSNCURSINRSM.2019.8888614

Sparse recovery with predictable accuracy in noisy spherical antenna near-field measurements

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