Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation

Cheng Yu Hung; Mostafa Kaveh

doi:10.1109/CAMSAP.2017.8313068

Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation

Cheng Yu Hung, Mostafa Kaveh

Administration (CSENG)

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

4 Scopus citations

Abstract

In this work, combined calibration and DoA estimation is approached as an extension of the formulation for the Single Measurement Vector (SMV) model of self-calibration to the Multiple Measurement Model (MMV) case. By taking advantage of multiple snapshots, a modified nuclear norm minimization problem is proposed to recover a low-rank larger dimension matrix. We also give the definition of a linear operator for the MMV model, and give its corresponding matrix representation to generate a variant of a convex optimization problem. In order to mitigate the computational complexity of the approach, singular value decomposition (SVD) is applied to reduce the problem size. The performance of the proposed methods are demonstrated by numerical simulations.

Original language	English (US)
Title of host publication	2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538612514
DOIs	https://doi.org/10.1109/CAMSAP.2017.8313068
State	Published - Mar 9 2018
Event	7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017 - Curacao Duration: Dec 10 2017 → Dec 13 2017

Publication series

Name	2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017
Volume	2017-December

Conference

Conference	7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017
City	Curacao
Period	12/10/17 → 12/13/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

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10.1109/CAMSAP.2017.8313068

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Hung, C. Y., & Kaveh, M. (2018). Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation. In 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017 (pp. 1-5). (2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017; Vol. 2017-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAMSAP.2017.8313068

Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation. / Hung, Cheng Yu; Kaveh, Mostafa.
2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-5 (2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017; Vol. 2017-December).

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

Hung, CY & Kaveh, M 2018, Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation. in 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017. 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017, vol. 2017-December, Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017, Curacao, 12/10/17. https://doi.org/10.1109/CAMSAP.2017.8313068

Hung CY, Kaveh M. Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation. In 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-5. (2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017). doi: 10.1109/CAMSAP.2017.8313068

Hung, Cheng Yu ; Kaveh, Mostafa. / Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation. 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-5 (2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017).

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Low rank matrix recovery for joint array self-calibration and sparse model DoA estimation

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