Experimental aeroacoustics is concerned with the estimation of acoustic source power distributions, which are for instance caused by fluid structure interactions on scaled aircraft models inside a wind tunnel, from microphone array measurements of associated sound pressure fluctuations. In the frequency domain aeroacoustic sound propagation can be modelled as a random source problem for a convected Helmholtz equation. This article is concerned with the inverse random source problem to recover the support of an uncorrelated aeroacoustic source from correlations of observed pressure signals. We show that a variant of the factorization method from inverse scattering theory can be used for this purpose. We also discuss a surprising relation between the factorization method and a commonly used beamforming algorithm from experimental aeroacoustics, which is known as Capon's method or as the minimum variance method. Numerical examples illustrate our theoretical findings.
翻译:实验空气分析学涉及对声源动力分布的估计,例如,声源动力分布是由风道内天体模型上的流体结构相互作用造成的,这种变化来自对相关声压波动的麦克风阵列测量。在频率域中,大气声学声音传播可模拟为静电赫尔姆霍尔茨方程式的一个随机源问题。本文章涉及反向随机源问题,以从观察到的压力信号的相互关系中恢复一个与气源不相干源的支持。我们显示,反散射理论的因子化方法的变异可用于此目的。我们还讨论系数化方法与实验性大气仪学通常使用的波形算法(称为卡彭方法或最小差异法)之间的惊人关系。数字示例说明了我们的理论发现。