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 properties 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 a Point Spread Function and contains local minima, but can be improved with the proposed broadband optimization. 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. 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波束的延伸。 鉴于源位置、空间形状、多极旋转或流性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类似于点扩展函数, 包含本地微型功能, 但可以通过拟议的宽带优化加以改进。 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, 并从结果中重建光谱。 该文件显示, 合成单极相对于标准全球优化和 CLEAN- SC 而言, 该方法优于合成单极。 对于真实世界的数据来说, 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确定和整合感兴趣的区域。 显示, 通过使用合理的初始值, 全球优化问题会降低到本地优化问题, 从结果中重建光谱。 进一步显示, 合成单极能 显示, 和多极 显示, 显示, 拟议的方法能够向不同的极 。