Effect of Roughness on Object Identification Using OAM Spectrum

LiDAR detection is very sensitive to the surface roughness of objects, which will affect the detection and identification results of the objects. The orbital angular momentum (OAM) spectrum can also be used with LiDAR to detect objects, but there are currently no research papers analyzing the impact of roughness in this scenario. In this study, a roughness model and a projection measurement method were used for numerical simulation. The analysis showed that when the wavelength is 0.5 um <= lambda <= 1.5 um, and the correlation length is 1 mm, roughness does not affect the rotational symmetry of objects identified the OAM spectrum. When the correlation length is 5 mm and 10 mm, and the root mean square of the surface roughness is alpha < 0.7 lambda, the roughness does not affect the determination of the rotational symmetry of the target. Experimentally, this study built an optical architecture for detecting the symmetry of objects using OAM spectra. Using a 532 nm laser, the study measured five-leaf clover objects with four different roughness levels (320 mesh, 600 mesh, 2000 mesh, and 10,000 mesh). The experimental results show that using OAM spectra to detect the rotational symmetry of objects is insensitive to surface roughness, which is consistent with the simulation results. This study can promote the further application of orbital angular momentum in LiDAR target recognition.