Low complexity joint angle and delay estimation for underwater multipath acoustic channel based on sparse Bayesian learning

In the field of underwater acoustic communication, multipath signals arrive at the receiving end with different angles and path delays, which can cause degradation in communication quality. When performing angle-delay joint estimation, sparse Bayesian learning (SBL) has many advantages over traditio...

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Vydané v:	Applied acoustics Ročník 214; s. 109703
Hlavní autori:	Wang, Jinyang, Wang, Haibin, Bourennane, El-Bay, Madani, Mahdi, Tai, Yupeng, Wang, Jun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.11.2023 Elsevier
Predmet:	Engineering Sciences Joint angle and delay estimation Low complexity Signal and Image processing Sparse Bayesian learning Underwater acoustic communication Joint angle and delay estimation Low complexity Sparse Bayesian learning Underwater acoustic communication
ISSN:	0003-682X, 1872-910X
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Popis
Shrnutí:	In the field of underwater acoustic communication, multipath signals arrive at the receiving end with different angles and path delays, which can cause degradation in communication quality. When performing angle-delay joint estimation, sparse Bayesian learning (SBL) has many advantages over traditional methods, such as high accuracy, resolution and global minimum results, but at the cost of high computational complexity. Regarding this, in this study, we propose a low-complexity SBL based framework to jointly estimate the angle and delay of the received signal. We first propose a low-complexity approximation SBL algorithm applied to joint estimation, which can keep the super-resolution and estimation accuracy but significantly reduce the computation time. To further tackle the problem of performance degradation of the approximate algorithm in underwater low signal-to-noise ratio environments, we utilize above result as a starting point for the space-alternating generalized Expectation Maximization (SAGE) algorithm to achieve a more precise estimation. Simulation and experimental results demonstrate that the proposed algorithm has an excellent performance in various underwater multipath scenarios. •We first propose a low-complexity approximation SBL algorithm applied to joint angle and delay estimation.•It can keep the super-resolution and estimation accuracy but significantly reduce the computation time.•In low SNR environment, we use above result as a starting point for the SAGE algorithm for more precise estimation.•Simulation and experimental results demonstrate its excellent performance in various multipath environments.
ISSN:	0003-682X 1872-910X
DOI:	10.1016/j.apacoust.2023.109703