Liu, Tianyi ; Deram, Sai Pavan ; Ardah, Khaled ; Haardt, Martin ; Pfetsch, Marc E. ; Pesavento, Marius (2024)
Gridless Parameter Estimation in Partly Calibrated Rectangular Arrays.
49th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024). Seoul, Republic of Korea (14.-19.04.2024)
doi: 10.1109/ICASSP48485.2024.10446959
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Spatial frequency estimation from a mixture of noisy sinusoids finds applications in various fields. The widely used subspace-based methods provide super-resolution parameter estimation at a low computational cost. However, they require an accurate array calibration, which is difficult for large antenna arrays. Sparsity-based methods have been shown to be more robust than subspace-based methods in difficult scenarios, e.g., in the case with a small number of snapshots and/or correlated sources. In this paper, we consider the direction-of-arrival (DOA) estimation in partly calibrated rectangular arrays comprising several calibrated and identical subarrays. We derive a gridless sparse formulation for DOA estimation based on the shift-invariance properties of the array and develop an efficient algorithm in the alternating direction method of multipliers (ADMM) framework. Numerical simulations show the superior error performance of our proposed method compared to subspace-based methods.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Liu, Tianyi ; Deram, Sai Pavan ; Ardah, Khaled ; Haardt, Martin ; Pfetsch, Marc E. ; Pesavento, Marius |
| Art des Eintrags: | Bibliographie |
| Titel: | Gridless Parameter Estimation in Partly Calibrated Rectangular Arrays |
| Sprache: | Englisch |
| Publikationsjahr: | 18 März 2024 |
| Verlag: | IEEE |
| Buchtitel: | 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings |
| Veranstaltungstitel: | 49th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024) |
| Veranstaltungsort: | Seoul, Republic of Korea |
| Veranstaltungsdatum: | 14.-19.04.2024 |
| DOI: | 10.1109/ICASSP48485.2024.10446959 |
| Kurzbeschreibung (Abstract): | Spatial frequency estimation from a mixture of noisy sinusoids finds applications in various fields. The widely used subspace-based methods provide super-resolution parameter estimation at a low computational cost. However, they require an accurate array calibration, which is difficult for large antenna arrays. Sparsity-based methods have been shown to be more robust than subspace-based methods in difficult scenarios, e.g., in the case with a small number of snapshots and/or correlated sources. In this paper, we consider the direction-of-arrival (DOA) estimation in partly calibrated rectangular arrays comprising several calibrated and identical subarrays. We derive a gridless sparse formulation for DOA estimation based on the shift-invariance properties of the array and develop an efficient algorithm in the alternating direction method of multipliers (ADMM) framework. Numerical simulations show the superior error performance of our proposed method compared to subspace-based methods. |
| Freie Schlagworte: | Direction-of-arrival estimation, Array signal processing, Superresolution, Estimation, Signal processing algorithms, Numerical simulation, Frequency estimation, DOA estimation, joint sparsity, partly calibrated arrays, shift-invariance, ADMM |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Nachrichtentechnische Systeme 04 Fachbereich Mathematik 04 Fachbereich Mathematik > Optimierung 04 Fachbereich Mathematik > Optimierung > Discrete Optimization |
| Hinterlegungsdatum: | 23 Apr 2024 09:10 |
| Letzte Änderung: | 27 Sep 2024 10:24 |
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