Sparse and Structured Modelling of Underwater Acoustic Channel Impulse Responses
Yang, Chaoran LU ; Ling, Qing ; Sheng, Xueli ; Mu, Mengfei and Jakobsson, Andreas LU
(2023)
48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
- Abstract
In this paper, we consider real-time modelling of an underwater acoustic channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development to model acoustic channels using a Kronecker structure, we propose a sparse block updating conjugate gradient algorithm. The method initially compensate for the drift common in underwater measurements, to allow the CIR to be modelled as sparse, and then forms a first sparse structured update of the CIR. Should the signal-to-noise ratio of the measurement be high enough to allow for it, the estimate is then refined by relaxing first the assumed Kronecker structure, and then, if still improving the estimate, the sparsity assumption. The... (More)
In this paper, we consider real-time modelling of an underwater acoustic channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development to model acoustic channels using a Kronecker structure, we propose a sparse block updating conjugate gradient algorithm. The method initially compensate for the drift common in underwater measurements, to allow the CIR to be modelled as sparse, and then forms a first sparse structured update of the CIR. Should the signal-to-noise ratio of the measurement be high enough to allow for it, the estimate is then refined by relaxing first the assumed Kronecker structure, and then, if still improving the estimate, the sparsity assumption. The proposed method is evaluated using both simulated and measured underwater signals, clearly illustrating the preferable performance of the proposed method.
(Less)
- author
- Yang, Chaoran
LU
; Ling, Qing
; Sheng, Xueli
; Mu, Mengfei
and Jakobsson, Andreas
LU
- organization
-
- Mathematical Statistics
- Statistical Signal Processing Group (research group)
- eSSENCE: The e-Science Collaboration
- LTH Profile Area: Engineering Health
- LTH Profile Area: AI and Digitalization
- ELLIIT: the Linköping-Lund initiative on IT and mobile communication
- Biomedical Modelling and Computation (research group)
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Drift, Structured channel estimate, Time-varying impulse response, Underwater sonar
- host publication
- ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
- conference location
- Rhodes Island, Greece
- conference dates
- 2023-06-04 - 2023-06-10
- external identifiers
-
- scopus:86000371880
- ISBN
- 9781728163277
- DOI
- 10.1109/ICASSP49357.2023.10096650
- language
- English
- LU publication?
- yes
- id
- e1b38d06-d675-45aa-9e22-6669b313b1fe
- date added to LUP
- 2025-06-05 11:27:44
- date last changed
- 2025-06-05 14:07:37
@inproceedings{e1b38d06-d675-45aa-9e22-6669b313b1fe,
abstract = {{<p>In this paper, we consider real-time modelling of an underwater acoustic channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development to model acoustic channels using a Kronecker structure, we propose a sparse block updating conjugate gradient algorithm. The method initially compensate for the drift common in underwater measurements, to allow the CIR to be modelled as sparse, and then forms a first sparse structured update of the CIR. Should the signal-to-noise ratio of the measurement be high enough to allow for it, the estimate is then refined by relaxing first the assumed Kronecker structure, and then, if still improving the estimate, the sparsity assumption. The proposed method is evaluated using both simulated and measured underwater signals, clearly illustrating the preferable performance of the proposed method.</p>}},
author = {{Yang, Chaoran and Ling, Qing and Sheng, Xueli and Mu, Mengfei and Jakobsson, Andreas}},
booktitle = {{ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings}},
isbn = {{9781728163277}},
keywords = {{Drift; Structured channel estimate; Time-varying impulse response; Underwater sonar}},
language = {{eng}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Sparse and Structured Modelling of Underwater Acoustic Channel Impulse Responses}},
url = {{http://dx.doi.org/10.1109/ICASSP49357.2023.10096650}},
doi = {{10.1109/ICASSP49357.2023.10096650}},
year = {{2023}},
}