Obstacle inversion based on the self-healing property of structured light.

The self-healing property of structured light allows it to partially recover its original intensity distribution during propagation after a portion of its intensity has been obscured by an obstacle. In this study, we present a thorough investigation of the self-healing property of perfect vortex beam (PVB) within structured light. Firstly, we investigated the impact of obstacles of varying sizes and shapes on PVB at different stages of propagation, leading to a key conclusion the self-healing process of PVB can be divided into two parts: the self-healing of the obstructed region and the damage in the unstructured region. Secondly, we propose a novel structural metric as a precise and quantitative description of the self-healing property of structured light, equipped with adjustable parameters to cater to different self-healing demands. We also undertake an exploration of the self-healing mechanisms of structured light, utilizing the theory of wave-particle duality. Thirdly, drawing from our research findings, we propose a novel optical application model for obstacle inversion based on the self-healing property of structured light. This model accurately inverts the size and position of obstacles. Furthermore, we integrate convolutional neural networks into our obstacle inversion model, enabling successful inversion of obstacle size and position, even in scenarios with significant variations in the intensity information of structured light caused by oceanic turbulence. Our research has not only enhanced the comprehension of the self-healing mechanisms in structured light, but also established new avenues for its implementation in optical imaging, obstacle detection, and other fields.