|Table of Contents|

[1] Wu Feiyun, Zhou Yuehai, Tong Feng, Fang Shiliang, et al. Compressed sensing estimation of sparse underwateracoustic channels with a large time delay spread [J]. Journal of Southeast University (English Edition), 2014, 30 (3): 271-277. [doi:10.3969/j.issn.1003-7985.2014.03.003]
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Compressed sensing estimation of sparse underwateracoustic channels with a large time delay spread()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
30
Issue:
2014 3
Page:
271-277
Research Field:
Mathematics, Physics, Mechanics
Publishing date:
2014-09-30

Info

Title:
Compressed sensing estimation of sparse underwateracoustic channels with a large time delay spread
Author(s):
Wu Feiyun1;  Zhou Yuehai1;  Tong Feng1;  Fang Shiliang2
1Key Laboratory of Underwater Acoustic Communication and Marine Information Technologyof Minister of Education, Xiamen University, Xiamen 361005, China
2Key Laboratory of Underwater Acoustic Signal Processing of Minister of Education, Southeast University, Nanjing 210096, China
Keywords:
norm constraint;  sparse underwater acoustic channel;  compressed sensing
PACS:
TB567
DOI:
10.3969/j.issn.1003-7985.2014.03.003
Abstract:
The estimation of sparse underwater acoustic channels with a large time delay spread is investigated under the framework of compressed sensing. For these types of channels, the excessively long impulse response will significantly degrade the convergence rate and tracking capability of the traditional estimation algorithms such as least squares(LS), while excluding the use of the delay-Doppler spread function due to huge computational complexity. By constructing a Toeplitz matrix with a training sequence as the measurement matrix, the estimation problem of long sparse acoustic channels is formulated into a compressed sensing problem to facilitate the efficient exploitation of sparsity. Furthermore, unlike the traditional l1 norm or exponent-based approximation l0 norm sparse recovery strategy, a novel variant of approximate l0 norm called AL0 is proposed, minimization of which leads to the derivation of a hybrid approach by iteratively projecting the steepest descent solution to the feasible set. Numerical simulations as well as sea trial experiments are compared and analyzed to demonstrate the superior performance of the proposed algorithm.

References:

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Memo

Memo:
Biographies: Wu Feiyun(1984—), male, graduate; Tong Feng(corresponding author), male, doctor, professor, ftong@xmu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.11274259), the Open Project Program of the Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education(No.UASP1305).
Citation: Wu Feiyun, Zhou Yuehai, Tong Feng, et al. Compressed sensing estimation of sparse underwater acoustic channels with a large time delay spread[J].Journal of Southeast University(English Edition), 2014, 30(3):271-277.[doi:10.3969/j.issn.1003-7985.2014.03.003]
Last Update: 2014-09-20