Study of GSO-GL based secondary source configuration optimization method for broadband sound field reproduction

Yidong Liu, Kean Chen, Jian Xu, Lei Yang
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Abstract

Sound field reproduction is a method that uses multiple secondary sound sources to reproduce a predefined desired sound field in a listening area. The configuration of the secondary sound sources is a key factor affecting the reproduction performances. To optimize the secondary source configuration, this study proposes a new method that combines the Gram-Schmidt orthogonalization method with the group Lasso method, which is called GSO-GL method. Firstly, it selects a certain number of the secondary sources from all the alternative secondary sources using the Gram-Schmidt orthogonalization method. The excitation sources are then further selected from the secondary sources selected in the previous step using the group Lasso method. The sound field simulation from the 2D room model show that the GSO-GL method outperforms the Gram-Schmidt orthogonalization method or the group Lasso method alone, combining the high system stability of the Gram-Schmidt orthogonalization method with the high reproduction accuracy of the group Lasso method.
基于 GSO-GL 的宽带声场再现二次声源配置优化方法研究
声场再现是一种利用多个辅助声源在听音区域再现预定的理想声场的方法。二次声源的配置是影响重现效果的关键因素。为了优化二次声源配置,本研究提出了一种结合了格拉姆-施密特正交化方法和群拉索方法的新方法,即 GSO-GL 方法。首先,该方法使用格拉姆-施密特正交化方法从所有可供选择的二次激励源中选择一定数量的二次激励源。然后,使用群套索法从上一步选择的二次声源中进一步选择激励声源。二维房间模型的声场模拟结果表明,GSO-GL 方法结合了格拉姆-施密特正交化方法的高系统稳定性和群拉索方法的高再现精度,其效果优于单独使用格拉姆-施密特正交化方法或群拉索方法。
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