TY - GEN
T1 - Using Low-Complexity Adaptive Beamformer to Improve MIMO Sonar Imaging Performance
AU - Fan, Jiahao
AU - Zhao, Yacong
AU - Liu, Xionghou
AU - Yang, Yixin
AU - Sun, Chao
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - We present an improved MIMO sonar imaging method utilizing the low-complexity adaptive (LCA) beamformer. LCA beamformer can be regarded as a simplified version of the minimum variance distortionless response (MVDR) beamformer or an adaptive extension of the conventional beamformer (CBF). Although both MVDR and LCA aim to minimize the noise and interference in the imaging process, MVDR calculates the optimal beamformer weight from the spatial statistics of the wave field, while LCA selects the best weight from a set of pre-defined weights. In this paper, we use a set of Kaiser and Chebyshev windows for LCA to choose from. The Kaiser windows are used to suppress sidelobes (SLs), while the Chebyshev windows are used to improve the resolution. Numerical simulations demonstrate that the proposed MIMO sonar imaging method using LCA beamformer outperforms the one using CBF in terms of resolution and SLs. Compared with MVDR, LCA is more robust and has lower computational complexity, albeit with weaker performance than MVDR.
AB - We present an improved MIMO sonar imaging method utilizing the low-complexity adaptive (LCA) beamformer. LCA beamformer can be regarded as a simplified version of the minimum variance distortionless response (MVDR) beamformer or an adaptive extension of the conventional beamformer (CBF). Although both MVDR and LCA aim to minimize the noise and interference in the imaging process, MVDR calculates the optimal beamformer weight from the spatial statistics of the wave field, while LCA selects the best weight from a set of pre-defined weights. In this paper, we use a set of Kaiser and Chebyshev windows for LCA to choose from. The Kaiser windows are used to suppress sidelobes (SLs), while the Chebyshev windows are used to improve the resolution. Numerical simulations demonstrate that the proposed MIMO sonar imaging method using LCA beamformer outperforms the one using CBF in terms of resolution and SLs. Compared with MVDR, LCA is more robust and has lower computational complexity, albeit with weaker performance than MVDR.
KW - low-complexity adaptive beamformer
KW - MIMO sonar
KW - sonar imaging
KW - sonar signal processing
UR - http://www.scopus.com/inward/record.url?scp=85184802907&partnerID=8YFLogxK
U2 - 10.1109/ICICSP59554.2023.10390717
DO - 10.1109/ICICSP59554.2023.10390717
M3 - 会议稿件
AN - SCOPUS:85184802907
T3 - 2023 6th International Conference on Information Communication and Signal Processing, ICICSP 2023
SP - 1198
EP - 1202
BT - 2023 6th International Conference on Information Communication and Signal Processing, ICICSP 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Information Communication and Signal Processing, ICICSP 2023
Y2 - 23 September 2023 through 25 September 2023
ER -