This paper presents an extension to global optimization beamforming for acoustic broadband sources. Given, that properties such as the source location, spatial shape, multipole rotation, or flow conditions can be parameterized over the frequency, a CSM-fitting can be performed for all frequencies at the same time. A numerical analysis shows that the non-linear error function for the standard global optimization problem is similar to the source's Point Spread Function and contains local minima, but can be improved with the proposed broadband error. Not only increases the broadband optimization process the ratio of equations to unknown variables, but it also smooths out the cost function. It also simplifies the process of identifying sources and reconstructing their spectra from the results. The paper shows that the method is superior on synthetic monopoles compared to standard global optimization and CLEAN-SC. For real-world data the results of broadband global optimization, standard global optimization, and CLEAN-SC are similar. However, the proposed method does not require the identification and integration of Regions Of Interest. Additionally it is shown, that by using reasonable initial values the global optimization problem reduces to a local optimization problem with similar results. Further, it is shown that the proposed method is able to identify multipoles with different pole amplitudes and unknown pole rotations.
翻译:本文展示了声频宽带源全球优化光束的延伸。 鉴于源位置、空间形状、多极旋转或流程条件等属性可以对频率进行参数化, 能够同时对所有频率进行 CSM 配置。 数字分析显示, 标准全球优化问题的非线性错误功能与源点扩展功能相似, 包含本地微小功能, 但可以通过拟议的宽带错误加以改进 。 不仅提高宽带优化进程方程式与未知变量的比例, 而且还可以平滑成本功能 。 它还简化了源的识别进程, 从结果中重建光谱。 该文件显示, 合成单极比标准全球优化和 CLEAN- SC 高。 真实世界数据中, 宽带全球优化、 标准全球优化和 CLEAN- SC 的结果类似 。 但是, 拟议的方法并不要求识别和整合感兴趣的区域。 此外, 显示, 通过使用合理的初始值, 全球优化问题降为本地优化问题, 从结果重建光谱的光谱, 显示合成单极比 。 此外, 显示, 显示, 与未知的极 能够显示, 显示, 不同的极 显示, 显示, 与 不同的 以 不同的 。