Improved high-precision approach based on deconvolution in MIMO sonar imagery
Multiple-input multiple-output (MIMO) sonar enables high-resolution imaging, which is extremely useful in underwater acoustic high-precision imagery. However, the first peak sidelobe levels and beamwidth performance degrade significantly when conventional tapering is applied due to the non-uniformit...
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doaj-94936f81a72d4ae0939d5a3771da7def2021-04-02T12:45:52ZengWileyThe Journal of Engineering2051-33052019-12-0110.1049/joe.2019.0994JOE.2019.0994Improved high-precision approach based on deconvolution in MIMO sonar imageryLu Yan0Shengchun Piao1Feng Xu2College of Underwater Acoustic Engineering, Harbin Engineering UniversityCollege of Underwater Acoustic Engineering, Harbin Engineering UniversityInstitute of Acoustic ChineseMultiple-input multiple-output (MIMO) sonar enables high-resolution imaging, which is extremely useful in underwater acoustic high-precision imagery. However, the first peak sidelobe levels and beamwidth performance degrade significantly when conventional tapering is applied due to the non-uniformity of the spanned virtual linear array, which prevents MIMO sonar from obtaining high-precision images with high resolution and high definition. Therefore, an improved high-precision approach in MIMO sonar imagery is proposed based on deconvolution to realise sidelobe suppression and to narrow the mainlobe width. The relationship between the target's beam power function and the pattern of the actual transmitting–receiving arrays is derived first, and design criteria are presented for MIMO sonar arrays to enhance the resolution. Subsequently, according to the orthogonality of the transmitting signals, the echo is separated by matched filtering, and then joint beamforming is employed to attain the beam data. Finally, the focused images are processed by deconvolution to enhance the clarity of the image and simultaneously obtain higher resolution. Numerical simulations and lake experiments are presented to demonstrate that high-precision images in MIMO sonar are achieved utilising the proposed approach, which also involves a lower computation load.https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0994array signal processingradar imagingmatched filtersmimo communicationantenna arraysimage resolutionsonar arraysunderwater acoustic high-precision imagerypeak sidelobe levelsbeamwidth performance degradespanned virtual linear arrayhigh-precision imageshigh definitionhigh-precision approachmimo sonar imagerydeconvolutiontargetactual transmitting–receiving arrayshigh-resolution imagingmultiple-input multiple-output sonarfocused imagesmimo sonar arrays |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lu Yan Shengchun Piao Feng Xu |
spellingShingle |
Lu Yan Shengchun Piao Feng Xu Improved high-precision approach based on deconvolution in MIMO sonar imagery The Journal of Engineering array signal processing radar imaging matched filters mimo communication antenna arrays image resolution sonar arrays underwater acoustic high-precision imagery peak sidelobe levels beamwidth performance degrade spanned virtual linear array high-precision images high definition high-precision approach mimo sonar imagery deconvolution target actual transmitting–receiving arrays high-resolution imaging multiple-input multiple-output sonar focused images mimo sonar arrays |
author_facet |
Lu Yan Shengchun Piao Feng Xu |
author_sort |
Lu Yan |
title |
Improved high-precision approach based on deconvolution in MIMO sonar imagery |
title_short |
Improved high-precision approach based on deconvolution in MIMO sonar imagery |
title_full |
Improved high-precision approach based on deconvolution in MIMO sonar imagery |
title_fullStr |
Improved high-precision approach based on deconvolution in MIMO sonar imagery |
title_full_unstemmed |
Improved high-precision approach based on deconvolution in MIMO sonar imagery |
title_sort |
improved high-precision approach based on deconvolution in mimo sonar imagery |
publisher |
Wiley |
series |
The Journal of Engineering |
issn |
2051-3305 |
publishDate |
2019-12-01 |
description |
Multiple-input multiple-output (MIMO) sonar enables high-resolution imaging, which is extremely useful in underwater acoustic high-precision imagery. However, the first peak sidelobe levels and beamwidth performance degrade significantly when conventional tapering is applied due to the non-uniformity of the spanned virtual linear array, which prevents MIMO sonar from obtaining high-precision images with high resolution and high definition. Therefore, an improved high-precision approach in MIMO sonar imagery is proposed based on deconvolution to realise sidelobe suppression and to narrow the mainlobe width. The relationship between the target's beam power function and the pattern of the actual transmitting–receiving arrays is derived first, and design criteria are presented for MIMO sonar arrays to enhance the resolution. Subsequently, according to the orthogonality of the transmitting signals, the echo is separated by matched filtering, and then joint beamforming is employed to attain the beam data. Finally, the focused images are processed by deconvolution to enhance the clarity of the image and simultaneously obtain higher resolution. Numerical simulations and lake experiments are presented to demonstrate that high-precision images in MIMO sonar are achieved utilising the proposed approach, which also involves a lower computation load. |
topic |
array signal processing radar imaging matched filters mimo communication antenna arrays image resolution sonar arrays underwater acoustic high-precision imagery peak sidelobe levels beamwidth performance degrade spanned virtual linear array high-precision images high definition high-precision approach mimo sonar imagery deconvolution target actual transmitting–receiving arrays high-resolution imaging multiple-input multiple-output sonar focused images mimo sonar arrays |
url |
https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0994 |
work_keys_str_mv |
AT luyan improvedhighprecisionapproachbasedondeconvolutioninmimosonarimagery AT shengchunpiao improvedhighprecisionapproachbasedondeconvolutioninmimosonarimagery AT fengxu improvedhighprecisionapproachbasedondeconvolutioninmimosonarimagery |
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