High-resolution CLEAN-SC (HR-CLEAN-SC) with spherical microphone arrays is a promising technology for panoramic sound source identification. To further enhance the ability to resolve multiple closely spaced sources at low frequencies, filter-and-sum based HR-CLEAN-SC is proposed in this paper. Simulations and experiments demonstrate that the proposed approach is superior to the existing spherical harmonics beamforming based HR-CLEAN-SC. Its advantages benefit from the use of sound pressure weight vector with strong sidelobe suppression ability. Besides, the proposed approach is further combined with diagonal denosing algorithm to achieve strong anti-interference ability. Finally, two different source marker constraints are compared. Dynamic constraint outperforms fixed constraint with respect to sound source identification performance, but it requires the preparation and storage for the frequency spectrum of maximum sidelobe level as well as more elapsed time.

带有球形麦克风阵列的高分辨率 CLEAN-SC (HR-CLEAN-SC) 是一种很有前景的全景声源识别技术。为了进一步增强在低频下解析多个紧密间隔源的能力，本文提出了基于滤波器和求和的 HR-CLEAN-SC。仿真和实验表明，所提出的方法优于现有的基于球谐波束形成的 HR-CLEAN-SC。其优点得益于采用了具有较强旁瓣抑制能力的声压权向量。此外，所提出的方法进一步结合对角线去噪算法，以实现强大的抗干扰能力。最后，比较两个不同的源标记约束。动态约束在声源识别性能方面优于固定约束，