基于循环维纳滤波器的声学成像优化方法

Acoustic Imaging Optimization Method Based on Cyclic Wiener Filter

针对混响环境中背景噪声干扰导致循环平稳源重建精度不高的问题,基于循环维纳滤波器,结合贝叶斯近场声全息技术,提出了一种声学成像优化方法。通过麦克风阵列在声源的近场测量由声源辐射信号的声压,利用循环维纳滤波器对测量值进行去噪,从而实现对循环平稳信号的盲提取,再应用贝叶斯近场声全息技术在空间上重建循环平稳源。首先,通过仿真分析,系统地评估了盲信号提取算法的有效性。然后,通过开展声源重建实验,进一步验证了该声学成像优化方法的可行性。

Regarding the difficulty,caused by background noises,for the reconstruction of cyclostationary sources in noisy environments,based on the cyclic wiener filter,combined with Bayesian near-field acoustic holography technology,an improvement method for acoustic imaging was proposed.The sound pressure of the signal radiated by the sound source was measured by the microphone array in the near field of the sound source,and the measurement was denoised by the cyclic wiener filter to realize the blind extraction of the cyclostationary signal,the spatial distribution of the cyclostationary source was reconstructed within the further combined with the Bayesian near-field acoustic holography framework.First,the effectiveness of the blind signal extraction algorithm was assessed through simulation analysis.Then,the feasibility of the acoustic imaging optimization method was further verified by carrying out sound source reconstruction experiments.