为提高快速迭代收缩阈值算法(Fast Iterative Shrinkage-Thresholding Algorithm,FISTA)在反卷积波束形成中的空间分辨率以及计算速度,采用基于快速傅里叶变换的声学模型,引入过松弛方法和"贪婪"重启策略,提出两种改进的快速迭代收缩阈值算法,即基于快速傅里叶变换的过松弛单调快速迭代收缩阈值算法(Over-relaxed Monotone Fast Iterative Shrinkage-Thresholding Algorithm based on Fast Fourier Transform,FFT-OMFISTA)和基于快速傅里叶变换的"贪婪"快速迭代收缩阈值算法("Greedy"Fast Iterative Shrinkage-Thresholding Algorithm based on Fast Fourier Transform,FFT-GFISTA),并应用于反卷积波束形成的求解过程中.设计了单声源和双声源的仿真与实验,验证了所提算法的有效性与优越性.结果表明,两种所提算法都具有良好的性能,都能在声源定位中实现更高的空间分辨率以及更快的计算速度.
A high-resolution sound source localization method based on improved FISTA
In order to improve the spatial resolution and computational speed of the fast iterative shrinkage-thresholding algorithm(FISTA)in deconvolution beamforming,an acoustic model based on fast Fourier transform is adopted,and an over-relaxed method and a"greedy"restart strategy are introduced.Two improved fast iterative shrinkage-thresholding algorithms,namely the over-relaxed monotone fast iterative shrinkage-threshold algorithm based on fast Fourier transform(FFT-OMFISTA)and the"greedy"fast iterative shrinkage-thresholding algorithm based on fast Fourier transform(FFT-GFISTA),are proposed and applied to the solution process of deconvolution beamforming.The simulation and experiments for single and dual sound sources are designed in this paper to verify the effectiveness and superiority of the proposed algorithms.The results show that both of the proposed algorithms have good performance,achieving higher spatial resolution and faster computational speed in sound source localization.
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