标题： 基于刚性球形麦克风阵列的核岭回归声场估计 显示英文标题

标题： Kernel ridge regression based sound field estimation using a rigid spherical microphone array

摘要： 我们提出了一种基于核岭回归的声场估计方法，使用刚性球形麦克风阵列。 具有物理约束核函数的核岭回归，以及进一步适应于观测声场的核函数，已被证明是强大的工具。 然而，此类方法通常假设为开放球形麦克风阵列配置，即在观测或估计区域中不存在散射体。 另一方面，一些方法假设存在散射体，并尝试通过最小二乘公式消除其影响。 即使如此，这些方法通常不包含散射体的边界条件，这些边界条件未被假定为已知。 相比之下，我们利用了这里的散射体是一个刚性球体的事实。 也就是说，虚拟散射源的位置和边界条件都是明确的。 基于此，我们在核岭回归框架内制定了散射声场，并提出了一种结合边界约束的新声场表示方法。 所提出方法的有效性通过使用新开发的球形麦克风阵列进行的数值模拟和实际实验得到验证。 显示英文摘要

摘要： We propose a sound field estimation method based on kernel ridge regression using a rigid spherical microphone array. Kernel ridge regression with physically constrained kernel functions, and further with kernel functions adapted to observed sound fields, have proven to be powerful tools. However, such methods generally assume an open-sphere microphone array configuration, i.e., no scatterers exist within the observation or estimation region. Alternatively, some approaches assume the presence of scatterers and attempt to eliminate their influence through a least-squares formulation. Even then, these methods typically do not incorporate the boundary conditions of the scatterers, which are not presumed to be known. In contrast, we exploit the fact the scatterer here is a rigid sphere. Meaning, both the virtual scattering source locations and the boundary conditions are well-defined. Based on this, we formulate the scattered sound field within the kernel ridge regression framework and propose a novel sound field representation incorporating a boundary constraint. The effectiveness of the proposed method is demonstrated through numerical simulations and real-world experiments using a newly developed spherical microphone array.