TY - JOUR
T1 - High-angular- and range-resolution imaging using MIMO sonar with two-dimensional deconvolution
AU - Liu, Xionghou
AU - Yang, Yixin
AU - Sun, Chao
AU - Zhuo, Jie
AU - Wang, Yiwei
AU - Zhai, Qingyue
N1 - Publisher Copyright:
© 2023 The Authors. IET Radar, Sonar & Navigation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
PY - 2023/6
Y1 - 2023/6
N2 - A real-aperture high-resolution imaging method utilising a multiple-input multiple-output (MIMO) sonar with two-dimensional (2-D) deconvolution processing is proposed. Via derivation, the authors show that the conventional beamformer (CBF) output of the MIMO sonar can be approximately expressed as the 2-D convolution between the original angular and range distributions of scatterers and a 2-D point spread function (PSF). Hence, to improve the imaging performance degraded by the convolution effect, the 2-D Richardson-Lucy (R-L) algorithm is used to deconvolve the CBF output of the MIMO sonar. Specifically, the authors give the iteration formula of the 2-D R-L algorithm attached to the MIMO sonar, and take the absolute values of the CBF outputs of the virtual array as the deconvolution inputs. The analytical expression of the 2-D PSF is also given, which is designed as the angular- and range-domain (amplitude) responses of a far-field ideal scatterer located in the normal direction of the virtual array. Meanwhile, the authors point out that the mismatch made by the approximation may degrade the imaging performance, and suggest that a small number of iterations in the 2-D R-L algorithm can be used to alleviate the mismatch problem. Via numerical simulations and a tank experiment, the authors show that the proposed method can simultaneously increase the angular and range resolutions and suppress the sidelobes, when compared to the existing MIMO sonar imaging method.
AB - A real-aperture high-resolution imaging method utilising a multiple-input multiple-output (MIMO) sonar with two-dimensional (2-D) deconvolution processing is proposed. Via derivation, the authors show that the conventional beamformer (CBF) output of the MIMO sonar can be approximately expressed as the 2-D convolution between the original angular and range distributions of scatterers and a 2-D point spread function (PSF). Hence, to improve the imaging performance degraded by the convolution effect, the 2-D Richardson-Lucy (R-L) algorithm is used to deconvolve the CBF output of the MIMO sonar. Specifically, the authors give the iteration formula of the 2-D R-L algorithm attached to the MIMO sonar, and take the absolute values of the CBF outputs of the virtual array as the deconvolution inputs. The analytical expression of the 2-D PSF is also given, which is designed as the angular- and range-domain (amplitude) responses of a far-field ideal scatterer located in the normal direction of the virtual array. Meanwhile, the authors point out that the mismatch made by the approximation may degrade the imaging performance, and suggest that a small number of iterations in the 2-D R-L algorithm can be used to alleviate the mismatch problem. Via numerical simulations and a tank experiment, the authors show that the proposed method can simultaneously increase the angular and range resolutions and suppress the sidelobes, when compared to the existing MIMO sonar imaging method.
KW - sonar imaging
KW - sonar signal processing
KW - sonar target recognition
UR - http://www.scopus.com/inward/record.url?scp=85151459471&partnerID=8YFLogxK
U2 - 10.1049/rsn2.12393
DO - 10.1049/rsn2.12393
M3 - 文章
AN - SCOPUS:85151459471
SN - 1751-8784
VL - 17
SP - 991
EP - 1001
JO - IET Radar, Sonar and Navigation
JF - IET Radar, Sonar and Navigation
IS - 6
ER -