Multiple-snapshot Compressive Beamforming with Non-convex Sparse Constraints

DING Feilong; CHI Cheng; LI Yu; HUANG Haining

doi:10.11999/JEIT220017

Volume 44 Issue 6

Jun. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(6): 2071-2079

DING Feilong, CHI Cheng, LI Yu, HUANG Haining. Multiple-snapshot Compressive Beamforming with Non-convex Sparse Constraints[J]. Journal of Electronics & Information Technology, 2022, 44(6): 2071-2079. doi: 10.11999/JEIT220017

Citation:

DING Feilong, CHI Cheng, LI Yu, HUANG Haining. Multiple-snapshot Compressive Beamforming with Non-convex Sparse Constraints[J]. Journal of Electronics & Information Technology, 2022, 44(6): 2071-2079. doi: 10.11999/JEIT220017

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Multiple-snapshot Compressive Beamforming with Non-convex Sparse Constraints

doi: 10.11999/JEIT220017

DING Feilong^{1, 2, 3},
CHI Cheng^{1, 2},
LI Yu^{1, 2
,
,},
HUANG Haining^{1, 2}

1.
The Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2.
Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing, Chinese Academy of Sciences, Beijing 100190, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds: The National Natural Science Foundation of China (62001469)

Received Date: 2022-01-06
Rev Recd Date: 2022-05-24

Available Online: 2022-05-26

Publish Date: 2022-06-21

Abstract

Abstract

Compressive beamforming based on the minimax-concave penalty function constraint, compared with the traditional $ {l_1} $ norm compressive beamforming, can enhance the sparsity of the signal and obtain a more accurate Direction Of Arrival (DOA) estimation. However, under the background of strong noise, the azimuth estimation result of this algorithm is unstable. In response to this problem, a Multiple-Snapshot Compressed sensing BeamForming based on the constraint of the Minimax Concave Penalty (MCP-MCSBF) function is proposed. Through the joint processing of multiple snapshots, it provides better anti-noise performance and more accurate direction of arrival estimation results. The simulation results show that compared with other multi-snapshot direction of arrival estimation algorithms, the proposed algorithm provides better accuracy and higher angular resolution. The lake test results verify further the effectiveness of the proposed algorithm.
- Direction Of Arrival (DOA) estimation,
- Compressive beamforming,
- Minimax-concave penalty function,
- Multiple-snapshot

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References(24)

References

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