Improving performance of three-dimensional imaging sonars through deconvolution

Wang, Peng; Chi, Cheng; Liu, Jiyuan; Huang, Haining

doi:10.1016/j.apacoust.2020.107812

Cited by 9 publications

(5 citation statements)

References 23 publications

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“…Generally, for FLS, the angular dimension is obtained via conventional beamforming for a uniform linear array, and the range dimension is obtained via match filtering for a linear frequency modulated signal [7,8]. For the output envelopes of conventional beamforming and match filtering, the main-to-side ratio of both is approximately −13 dB [9,10].…”

Section: Introductionmentioning

confidence: 99%

“…Deconvolution algorithms have been proposed to improve the angular resolution in spatial spectrum estimation by processing beamformer output data. These methods were subsequently extended to high-frequency sonar imaging to achieve higher resolution in both the angular and range dimensions simultaneously [7,8,12,[22][23][24][25][26][27]. However, the deconvolution results require several iterations, and the performance is related to the number of iterations.…”

Section: Introductionmentioning

confidence: 99%

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Low-Sidelobe Imaging Method Utilizing Improved Spatially Variant Apodization for Forward-Looking Sonar

Yan,

Yang,

et al. 2024

Remote Sensing

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For two-dimensional forward-looking sonar imaging, high sidelobes significantly degrade the quality of sonar images. The cosine window function weighting method is often applied to suppress the sidelobe levels in the angular and range dimensions, at the expense of the main lobe resolutions. Therefore, an improved spatially variant apodization imaging method for forward-looking sonar is proposed, to reduce sidelobes without degrading the main lobe resolution in angular-range dimensions. The proposed method is a nonlinear postprocessing operation in which the raw complex-valued sonar image produced by a conventional beamformer and matched filter is weighted by a spatially variant coefficient. To enhance the robustness of the spatially variant apodization approach, the array magnitude and phase errors are calibrated to prevent the occurrence of beam sidelobe increase prior to beamforming operations. The analyzed results of numerical simulations and a lake experiment demonstrate that the proposed method can greatly reduce the sidelobes to approximately −40 dB, while the main lobe width remains unchanged. Moreover, this method has an extremely simple computational process.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Low-Sidelobe Imaging Method Utilizing Improved Spatially Variant Apodization for Forward-Looking Sonar

Yan,

Yang,

et al. 2024

Remote Sensing

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show abstract

“…Chao Ma et al [9] proposed a deconvolution algorithm applied in the field of active underwater acoustic detection based on spatiotemporal two-dimensional information, improving the resolution capability of DOA under active detection from both time and angle dimensions. Peng Wang et al [10] demonstrated that the output of conventional 3D beamforming can be represented as the convolution of the 2D array beam pattern used and the backscatter function of the imaging target in the far field and near field. They then used a deconvolution algorithm to improve the spatial resolution and suppress side lobes in the output of conventional beamforming.…”

Section: Introductionmentioning

confidence: 99%

A Robust Denoised Algorithm Based on Hessian–Sparse Deconvolution for Passive Underwater Acoustic Detection

Yin,

Li,

Wang

et al. 2023

JMSE

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Digital beamforming techniques find wide applications in the field of underwater acoustic array signal processing. However, their azimuthal resolution has long been constrained by the Rayleigh limit, consequently limiting their detection performance. In this paper, we propose a novel two-dimensional Hessian–sparse deconvolution algorithm based on image processing techniques. This method assumes a priori that the underwater acoustic bearing time record (BTR) images exhibit sparsity, and then it first constructs partial differential equations in the beamforming domain with sparsity-norm constraints for optimal noise reduction. Subsequently, a two-dimensional deconvolution operation is applied to narrow the main lobe, aiming to achieve additional temporal gains in two-dimensional processing. The simulation and real sea trial data processing results show that the main lobe width of the proposed method is about 1.3 degrees at 0 dB. It effectively reduces the main lobe width and enhances the detection resolution of BTRs in the post-processing part, especially in low-signal-to-noise-ratio (SNR) environments. Therefore, the proposed method provides nice opportunities to further improve the target-detecting ability of hydrophone arrays.

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“…Generally, for FLS, the angular dimension is obtained by convention beamforming for a uniform linear array, and the range dimension is obtained by match filtering for a linear frequency modulated signal [7,8]. For the output envelopes of convention beamforming and match filtering, the main-toside ratio of both is approximately -13dB [9,10].…”

Section: Introductionmentioning

confidence: 99%

“…Deconvolution algorithms are proposed to improve the angular resolution in spatial spectrum estimation by processing the beamformers' output data. Then, the methods are extended to highfrequency sonar imaging to achieve higher resolution in both the angular and range dimensions simultaneously [7,8,12,[22][23][24][25][26][27]. However, the deconvoluted results require several iterations, and the performance is related to the number of iterations.…”

Section: Introductionmentioning

confidence: 99%

Low-sidelobe Imaging Method Utilizing Improved Spatially Variant Apodization for Forward-Looking Sonar

Yan,

Yang,

et al. 2023

Preprint

View full text Add to dashboard Cite

For two-dimensional forward-looking sonar imaging, high sidelobes significantly degrade the quality of sonar images. The cosine window function weighting method is often applied to suppress the sidelobe levels in the angular and range dimensions at the expense of the main lobe resolutions. Therefore, the improved spatially variant apodization imaging method for forward-looking sonar is proposed to reduce the sidelobes without degrading the main lobe resolution in angular-range dimensions. The proposed method is a nonlinear post-processing operation in which the raw complex-valued sonar image produced by a conventional beamformer and matched filter is weighted by a spatially variant coefficient. To enhance the robustness of the spatially variant apodization approach, the array magnitude and phase errors are calibrated to prevent beam sidelobe heightening from occurring prior to beamforming operations. The analyzed results of numerical simulations and a lake experiment demonstrate that the proposed method can greatly reduce the sidelobes to approximately -40 dB, while the main lobe width remains unchanged. Moreover, this method has an extremely simple computational process.

show abstract

Improving performance of three-dimensional imaging sonars through deconvolution

Cited by 9 publications

References 23 publications

Low-Sidelobe Imaging Method Utilizing Improved Spatially Variant Apodization for Forward-Looking Sonar

Low-Sidelobe Imaging Method Utilizing Improved Spatially Variant Apodization for Forward-Looking Sonar

A Robust Denoised Algorithm Based on Hessian–Sparse Deconvolution for Passive Underwater Acoustic Detection

Low-sidelobe Imaging Method Utilizing Improved Spatially Variant Apodization for Forward-Looking Sonar

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