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Remote Sensing
Volume 16
Issue 3
10.3390/rs16030476
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Article

Detecting Weak Underwater Targets Using Block Updating of Sparse and Structured Channel Impulse Responses

by
Chaoran Yang
1,2,3,
Qing Ling
1,2,3,
Xueli Sheng
1,2,3,*,
Mengfei Mu
1,2,3 and
Andreas Jakobsson
4
1
National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China
2
Key Laboratory for Polar Acoustics and Application of Ministry of Education, Harbin Engineering University, Ministry of Education, Harbin 150001, China
3
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China
4
Center for Mathematical Statistics, Lund University, 22100 Lund, Sweden
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(3), 476; https://doi.org/10.3390/rs16030476
Submission received: 14 December 2023 / Revised: 16 January 2024 / Accepted: 18 January 2024 / Published: 26 January 2024
(This article belongs to the Special Issue Advanced Array Signal Processing for Target Imaging and Detection)
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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 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.
Keywords: time-varying impulse response; drift compensation; structured channel estimate; underwater sonar; weak target detection time-varying impulse response; drift compensation; structured channel estimate; underwater sonar; weak target detection

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MDPI and ACS Style

Yang, C.; Ling, Q.; Sheng, X.; Mu, M.; Jakobsson, A. Detecting Weak Underwater Targets Using Block Updating of Sparse and Structured Channel Impulse Responses. Remote Sens. 2024, 16, 476. https://doi.org/10.3390/rs16030476

AMA Style

Yang C, Ling Q, Sheng X, Mu M, Jakobsson A. Detecting Weak Underwater Targets Using Block Updating of Sparse and Structured Channel Impulse Responses. Remote Sensing. 2024; 16(3):476. https://doi.org/10.3390/rs16030476

Chicago/Turabian Style

Yang, Chaoran, Qing Ling, Xueli Sheng, Mengfei Mu, and Andreas Jakobsson. 2024. "Detecting Weak Underwater Targets Using Block Updating of Sparse and Structured Channel Impulse Responses" Remote Sensing 16, no. 3: 476. https://doi.org/10.3390/rs16030476

APA Style

Yang, C., Ling, Q., Sheng, X., Mu, M., & Jakobsson, A. (2024). Detecting Weak Underwater Targets Using Block Updating of Sparse and Structured Channel Impulse Responses. Remote Sensing, 16(3), 476. https://doi.org/10.3390/rs16030476

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