Spatiotemporal two-dimensional deconvolution beam imaging technology

Ma, Chunguang; Sun, Dong; Mei, Jidan; Teng, Tingting

doi:10.1016/j.apacoust.2021.108310

Cited by 8 publications

(8 citation statements)

References 9 publications

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“…To mitigate the signal energy leakage in the azimuth, conventional beamforming is combined with the R-L deconvolution algorithm to estimate the target's azimuth of direction [27][28][29][30]. In this method, the beam pattern is treated as a point scattering function (PSF) in deconvolution, and the target azimuth is determined using the R-L iterative algorithm.…”

Section: Introductionmentioning

confidence: 99%

A Frequency–Azimuth Spectrum Estimation Method for Uniform Linear Array Based on Deconvolution

Lu,

Cai,

Guo

et al. 2024

Remote Sensing

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The frequency–azimuth (FRAZ) spectrum is a critical characteristic in passive target detection and tracking, as it encapsulates information regarding the signal’s frequency and azimuth. However, due to the inherent limitations in the sonar array’s physical aperture and the analysis time of the system, the signal often suffers from undersampling in both spatial and temporal dimensions. This undersampling leads to energy leakage across the azimuth and frequency domains, adversely affecting the resolution of the FRAZ spectrum. Such a reduction in resolution hampers multitarget resolution and feature extraction. To address these challenges, this study introduces a deconvolution-based FRAZ spectrum estimation method tailored for uniform linear arrays. The proposed method initiates by decoupling the azimuth and frequency in the FRAZ spectrum, forming a two-dimensional point scattering function that possesses shift-invariance. Subsequent to this, the power spectrum and the two-dimensional point scattering function undergo deconvolution using the Richardson–Lucy (R–L) iterative algorithm. The final stage involves calculating the signal azimuths and frequencies based on the deconvolution results from the preceding step. Comparative analyses involving simulations and sea test results reveal that the proposed method achieves a narrower main lobe width and diminished background noise in contrast to traditional FRAZ spectrum estimation techniques. This improvement is instrumental in minimizing the target’s energy leakage in both the azimuth and frequency domains.

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Section: Introductionmentioning

confidence: 99%

A Frequency–Azimuth Spectrum Estimation Method for Uniform Linear Array Based on Deconvolution

Lu,

Cai,

Guo

et al. 2024

Remote Sensing

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“…Simulation results showed that the proposed method produced a better beamforming performance for coherent targets compared to intensity-based deconvolution methods. 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.…”

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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“…Typically, in practical engineering, the ratio is needed to be approximately -40 dB to acquire high-quality sonar images. In practice, high sidelobe levels from a strong target echo can weaken or even completely mask the main lobe of a smaller target echo, so additional sidelobe suppression for FLS images is essential [11,12].…”

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

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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, 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.

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Spatiotemporal two-dimensional deconvolution beam imaging technology

Cited by 8 publications

References 9 publications

A Frequency–Azimuth Spectrum Estimation Method for Uniform Linear Array Based on Deconvolution

A Frequency–Azimuth Spectrum Estimation Method for Uniform Linear Array Based on Deconvolution

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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