Toward Photonic Orbital Angular Momentum as a Remote Sensing Modality through Random Media

Abstract

Within the last few decades, the spatial degree of freedom of light has gained significant attention in the form of photonic orbital angular momentum (OAM). The use of OAM for remote sensing has been of significant interest due to its inherent orthogonality that can be used for spatial frequency filtering, coherence filtering, and as both an active or passive sensing modality. Beams with OAM also contain interesting propagation properties that have potential to be more robust than non-OAM counterparts. One application of remote sensing is using OAM to measure the strength of optical phase distortions through random media that can contain turbulence or particulate matter. There has been significant work done on the subject, but there have been difficulties at creating an applicable OAM based sensing technique employed for use in an outdoor environment. This work develops an active OAM sensing modality denoted as Optical Heterodyne Detection of Orthogonal OAM Modes (OHDOOM) to reduce the optical receiver hardware based on a beatnote signal for the first time. The beatnote signal is then hypothesized to return information about the propagation environment by measuring the crosstalk between OAM modes due to channel perturbations. OHDOOM results through an emulated turbulent medium show that our method is highly sensitive to weak and strong turbulence depending on the transmitted OAM mode. Within a turbid medium, OHDOOM is believed to be sensitive to particles larger than the wavelength and insensitive to smaller particles. Experimental results agree well with simulated environmental conditions using wave optic simulations (WOS) implementing phase screens. A WOS for a turbulent medium is derived from turbulent phase statistics based on refractive index fluctuations. However, for the first time, a turbid medium's phase statistics are derived from a solution to the radiative transfer equation within the paraxial approximation.