摘要
为提高最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)波束形成算法的方位分辨能力,本文将MVDR算法的输出功率谱重新建模为卷积的形式,并运用两种解卷积技术对MVDR的方位谱进行后处理。该算法将角度空间中心位置的单个声源的MVDR方位谱当作点扩散函数(Point Spreading Function,PSF),并运用Richardson-Lucy算法和快速迭代收缩阈值算法(Fast Iterative Shrinkage-Thresholding Algorithm,FISTA)分别对MVDR(MVDR-RL,MVDR-FISTA)的方位谱进行解卷积后处理,获得背景级更低的MVDR-RL和MVDR-FISTA方位谱,同时提高了分辨能力和估计精度。仿真实验显示了所提算法的良好性能。
In order to improve the azimuth estimation capability of the minimum variance distortionless response(MVDR)beamforming algorithm,the output power spectrum of the MVDR algorithm was reformed as a convolution form,two deconvolution post-processing techniques were proposed to deconvolve the azimuth spectrum of MVDR.The algorithms take the MVDR azimuth spectrum of a single sound source at the center of the angular space as a point spreading function(PSF),and use the Richardson-Lucy algorithm and the fast iterative shrinkage-thresholding algorithm(FISTA)to deconvolute the MVDR(MVDR-RL,MVDR-FISTA)azimuth spectrum.The MVDR-RL and MVDR-FISTA azimuth spectrum has lower background level,higher resolution,and higher estimation accuracy.Simulation experiments show the good performance of the proposed algorithm.
作者
宋其岩
马晓川
李璇
詹飞
SONG Qiyan;MA Xiaochuan;LI Xuan;ZHAN Fei(Institute of Acoustics,Chinese Academy of Sciences,Key Laboratory of Underwater Vehicle Information Technology,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《信号处理》
CSCD
北大核心
2022年第1期9-18,共10页
Journal of Signal Processing
基金
中科院青促会资助。
关键词
最小方差无失真响应
解卷积
Richardson-Lucy
快速迭代收缩阈值
方位估计
minimum variance distortionless response
deconvolution
Richardson-Lucy
fast iterative shrinkage-thresholding algorithm
direction of arrival estimation
