Detecting Weak Underwater Targets Using Block Updating of Sparse and Structured Channel Impulse Responses
Yang, Chaoran ; Ling, Qing ; Sheng, Xueli ; Mu, Mengfei and Jakobsson, Andreas LU
(2024)
In Remote Sensing
16(3).
- Abstract
In this paper, we considered the real-time modeling of an underwater channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development in the modeling of acoustic channels using a Kronecker structure, we approximated the CIR using a structured and sparse model, allowing for a computationally efficient sparse block-updating algorithm, which can track the time-varying CIR even in low signal-to-noise ratio (SNR) scenarios. The algorithm employs a conjugate gradient formulation, which enables a gradual refinement if the SNR is sufficiently high to allow for this. This was performed by gradually relaxing the assumed Kronecker structure, as well as the sparsity assumptions, if... (More)
In this paper, we considered the real-time modeling of an underwater channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development in the modeling of acoustic channels using a Kronecker structure, we approximated the CIR using a structured and sparse model, allowing for a computationally efficient sparse block-updating algorithm, which can track the time-varying CIR even in low signal-to-noise ratio (SNR) scenarios. The algorithm employs a conjugate gradient formulation, which enables a gradual refinement if the SNR is sufficiently high to allow for this. This was performed by gradually relaxing the assumed Kronecker structure, as well as the sparsity assumptions, if possible. The estimated CIR was further used to form a residual signal containing (primarily) information of the time-varying signal responses, thereby allowing for the detection of weak target signals. The proposed method was evaluated using both simulated and measured underwater signals, clearly illustrating the better performance of the proposed method.
(Less)
- author
- Yang, Chaoran
; Ling, Qing
; Sheng, Xueli
; Mu, Mengfei
and Jakobsson, Andreas
LU
- organization
- publishing date
- 2024-02
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- drift compensation, structured channel estimate, time-varying impulse response, underwater sonar, weak target detection
- in
- Remote Sensing
- volume
- 16
- issue
- 3
- article number
- 476
- publisher
- MDPI AG
- external identifiers
-
- scopus:85184700857
- ISSN
- 2072-4292
- DOI
- 10.3390/rs16030476
- language
- English
- LU publication?
- yes
- id
- 5fd43fb4-fb1d-4f69-b3e1-9aa96825177e
- date added to LUP
- 2024-02-22 15:33:37
- date last changed
- 2024-02-22 15:33:37
@article{5fd43fb4-fb1d-4f69-b3e1-9aa96825177e,
abstract = {{<p>In this paper, we considered the real-time modeling of an underwater channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development in the modeling of acoustic channels using a Kronecker structure, we approximated the CIR using a structured and sparse model, allowing for a computationally efficient sparse block-updating algorithm, which can track the time-varying CIR even in low signal-to-noise ratio (SNR) scenarios. The algorithm employs a conjugate gradient formulation, which enables a gradual refinement if the SNR is sufficiently high to allow for this. This was performed by gradually relaxing the assumed Kronecker structure, as well as the sparsity assumptions, if possible. The estimated CIR was further used to form a residual signal containing (primarily) information of the time-varying signal responses, thereby allowing for the detection of weak target signals. The proposed method was evaluated using both simulated and measured underwater signals, clearly illustrating the better performance of the proposed method.</p>}},
author = {{Yang, Chaoran and Ling, Qing and Sheng, Xueli and Mu, Mengfei and Jakobsson, Andreas}},
issn = {{2072-4292}},
keywords = {{drift compensation; structured channel estimate; time-varying impulse response; underwater sonar; weak target detection}},
language = {{eng}},
number = {{3}},
publisher = {{MDPI AG}},
series = {{Remote Sensing}},
title = {{Detecting Weak Underwater Targets Using Block Updating of Sparse and Structured Channel Impulse Responses}},
url = {{http://dx.doi.org/10.3390/rs16030476}},
doi = {{10.3390/rs16030476}},
volume = {{16}},
year = {{2024}},
}