Occluded target detection of streak tube imaging lidar using image inpainting

We improve the system of multi-slit streak tube imaging lidar (MS-STIL) for occluded target detection. To solve the contradiction between high range resolution and deep depth of field, a fiber-optic beam, called 'beam shunting', is designed. In addition, we combine the deep-learning-based image inpainting algorithm with the MS-STIL to solve the problem of ineffective imaging when the target is obscured by a large area. Finally, the results of the simulated contrast experiments show that the range resolution is increased from 0.4 m to 0.1 m, and the new system is effective in detecting occluded targets.