全变分约束的解卷积常规波束形成方位谱估计算法

Total variation constrained deconvolved conventional beamforming algorithm for azimuthal spectral estimation

杨泽慧 ¹聂炜航 ¹程高峰 ²吴姚振 ³徐及 ¹赵庆卫 ¹颜永红¹

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作者信息

1. 中国科学院语音与智能信息处理实验室(声学研究所)北京 100190;中国科学院大学北京 100049
2. 中国科学院语音与智能信息处理实验室(声学研究所)北京 100190
3. 中国人民解放军91001部队北京 100084
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摘要

为了提高解卷积常规波束形成(D-CBF)算法的稳定性,降低方位谱背景噪声级,提高处理增益,提出了一种基于全变分约束的解卷积常规波束形成(TVD-CBF)空间谱估计算法.该方法利用声源分布的稀疏先验,在代价函数中加入总变分正则化项作为非线性约束,获得TVD-CBF算法的方位谱,从而在提升空间分辨率的同时,抑制噪声及误差的累积,提高求解的稳定性.仿真表明,该方法在D-CBF算法的基础上进一步提升了方位指向性和分辨率,具有良好的波达方向估计性能.海试数据处理结果表明,TVD-CBF方法在提升空间分辨率的同时,降低了空间谱的背景级,具有良好的方位估计性能.

Abstract

In order to enhance the stability of the deconvolved conventional beamforming(D-CBF)algorithm,reduce background noise levels in the azimuth spectrum,and improve processing gain,a total variation constrained deconvolved CBF(TVD-CBF)spatial spectrum estimation algorithm is proposed.The approach leverages the sparse prior of the source distribution by incorporating a total variation regularization term as a nonlinear constraint within the cost function.Consequently,spatial resolution is improved while the accumulation of noise and errors is suppressed,thereby enhancing solution stability.Simulation results demonstrate that the TVD-CBF algorithm significantly outperforms the D-CBF algorithm in terms of azimuthal directivity and resolution,exhibiting surperior performance in direction of arrival estimation.The effectiveness of the TVD-CBF algorithm is further validated through experiments on sea trial data.

关键词

方位谱估计/波达方向估计/常规波束形成/解卷积/全变分

Key words

Azimuthal spectral estimation/Direction of arrival estimation/Conventional beamforming/Deconvolution/Total variation

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出版年

2025

声学学报

中科院声学所

声学学报

CSCD北大核心

影响因子：0.802

ISSN：0371-0025

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