Vortex beams carrying orbital angular momentum (OAM) possess infinite-dimensional orthogonal eigenstates, rendering them exceptionally valuable for optical communication and information transmission applications. However, the sorting and recognition of OAM encounter formidable challenges in practical scenarios, especially when propagating through dynamic scattering media. Mode mixing and decoherence induced by time-varying perturbations severely restrict the effective exploitation of OAM. Traditional studies have predominantly focused on the interaction between vortex beams and static scattering media. Even for dynamic scattering media, existing investigations generally rely on synchronous speckle acquisition or deep learning for information retrieval, which inevitably results in complex system configurations or prohibitive computational overheads. To address these issues, this paper proposes an OAM sorting and recognition method for randomly rotating scattering media. By integrating the angularly averaged intensity cross-correlation function with a normalized cross-correlation screening (NCCS) algorithm, we establish a mapping relationship between the topological charge difference and the characteristic features of the cross-correlation ring (CCR). Furthermore, complete sorting and recognition of OAM modes are realized through the dual-reference perfect vortex beam (DRPVB) approach. Experimental results demonstrate that our method successfully overcomes the technical limitations of conventional synchronous speckle acquisition, enabling OAM sorting and recognition under randomly rotating media conditions and thus facilitating the practical application of vortex beams in optical communication and information processing applications.
Wang et al. (Thu,) studied this question.