This paper explores the advantages of combining asynchronous microphone array measurements for acoustic source mapping in two and three–dimensional applications. Four different approaches are considered, three consisting of the combination of the source maps (arithmetic mean, geometric mean, and minimum value), and a fourth one obtained by combining the cross–spectral matrices of all the asynchronous measurements into a larger matrix and applying beamforming with it. Both synthetic and experimental test cases convey enhanced results concerning the single measurement baseline, especially by reducing the spurious sidelobes. Two aeroacoustic experiments are considered, the first features a distributed sound source over a flat plate model tested in a wind tunnel and the second features a hovering drone with multiple sound sources, representing typical challenges for 2D and 3D source localization, respectively. For the 2D source mapping configuration, the sidelobe level was reduced up to 5 dB with respect to the baseline, while maintaining a similar beamwidth of the main lobe. For the 3D test cases, the approaches enable volumetric source mapping capabilities, even when planar microphone arrays are considered, commonly available in typical test facilities. Overall, the minimum value approach presents the best performance for all cases in terms of reduced main lobe beamwidth and sidelobe levels.

本文探讨了结合异步麦克风阵列测量在二维和三维应用中进行声源映射的优势。考虑了四种不同的方法，其中三种包括源图的组合（算术平均值、几何平均值和最小值），第四种是通过将所有异步测量的交叉谱矩阵组合成一个更大的矩阵并应用波束成形。合成和实验测试案例都传达了关于单一测量基线的增强结果，特别是通过减少虚假旁瓣。考虑了两个气动声学实验，第一个特征是在风洞中测试的平板模型上的分布式声源，第二个特征是具有多个声源的悬停无人机，分别代表 2D 和 3D 源定位的典型挑战。对于 2D 源映射配置，旁瓣电平相对于基线降低了 5 dB，同时保持了与主瓣相似的波束宽度。对于 3D 测试案例，即使考虑平面麦克风阵列，这些方法也可以实现体积源映射功能，通常在典型测试设施中可用。总体而言，最小值方法在减少主瓣波束宽度和旁瓣电平方面对所有情况都具有最佳性能。即使在考虑平面麦克风阵列的情况下，这些方法也可以实现体积源映射功能，在典型的测试设施中通常可用。总体而言，最小值方法在减少主瓣波束宽度和旁瓣电平方面对所有情况都具有最佳性能。即使在考虑平面麦克风阵列的情况下，这些方法也可以实现体积源映射功能，在典型的测试设施中通常可用。总体而言，最小值方法在减少主瓣波束宽度和旁瓣电平方面对所有情况都具有最佳性能。