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 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,空气声学声音传播可模拟为静电赫尔姆霍尔茨方程式的随机源问题。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与气源不相干源的支持。我们展示了反散射理论的因子化方法变量,可用于此目的。我们还讨论了系数化方法与实验性大气学(称为卡彭方法或最小差异法)通常使用的波形算法之间的惊人关系。数字示例说明了我们的理论发现。