基于稳定双共轭梯度的车内声场靶向重建方法

Targeted Reproduction Method of Interior Sound Field Based on Stabilized Biconjugate Gradient

摘要:

针对驾乘人员对车辆声学环境的智能化管控需求，基于稳定双共轭梯度（BiCGSTAB）提出一种协同提升声学能量对比度和声场平面性的车内声场靶向重建方法。首先，通过定义声场重建相关的声学问题，结合目标区域声压级响应关于声源分布位置的参数化结果，构建了面向驾乘人员的车内声学模型。其次，围绕期望声场目标搭建车内声场靶向重建框架，基于BiCGSTAB对车载声源驱动信号进行了迭代求解，并聚焦声学能量对比度、平面性等指标分析了车内声场重建性能。结果表明，该方法有效避免了声学复线性方程组求解的收敛异常问题，能够在车内目标区域实现声学幅值与相位信息的高聚焦重建。

Abstract:

Aiming at requirements of intelligent modulation in vehicle acoustic environment for drivers and passengers，a targeted sound field reproduction method is proposed based on stabilized biconjugate gradient （BiCGSTAB） to collectively improve the acoustic energy contrast and sound field planarity. Considering parametric results of the contribution weight on the in-vehicle sound acoustic arrays to the acoustic environment， and combining the automotive scenario to divide the target acoustic regions， the cabin acoustics model for the drivers and passengers are first constructed. By defining the acoustics problems related to sound field reproduction and combining with the parametric results that the sound pressure response of target regions with respect to sound source distribution positions， the interior acoustics model for drivers and passengers is constructed. Furthermore， the targeted reproduction framework of interior sound field is constructed embracing the given expected sound field， and the driving signals of sound sources are iteratively obtained based on BiCGSTAB. Focusing on acoustics energy contrast， sound field planarity and other indicators， the interior sound field reproduction performance is analyzed in detail. The results show that the proposed method can effectively avoid the abnormal convergence in solving the acoustics complex linear equations， and can achieve the high-quality reproduction about the acoustics amplitude and phase information in vehicle target regions