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

作　　者：杨泽慧 聂炜航 程高峰 吴姚振 徐及[1,2] 赵庆卫 颜永红[1,2] YANG Zehui;NIE Weihang;CHENG Gaofeng;WU Yaozhen;XU Ji;ZHAO Qingwei;YAN Yonghong(Speech and Intelligent Information Processing Laboratory,Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190;University of Chinese Academy of Sciences,Beijing 100049;Troops 91001,PLA,Beijing 100084)

机构地区：[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 [2]中国科学院大学,北京100049 [3]中国人民解放军91001部队,北京100084

出　　处：《声学学报》2025年第1期68-76,共9页Acta Acustica

基　　金：国家重点研发计划项目(2021YFC3101403)资助。

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。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 

分 类 号：TN911.7[电子电信—通信与信息系统]