Analysis of the performance of a polarized LiDAR imager in fog
This paper focuses on exploring ways to improve the performance of LiDAR imagers through fog. One of the known weaknesses of LiDAR technology is the lack of tolerance to adverse environmental conditions, such as the presence of fog, which hampers the future development of LiDAR in several markets. W...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/375699 |
| Acceso en línea: | https://hdl.handle.net/2117/375699 https://dx.doi.org/10.1364/OE.471872 |
| Access Level: | acceso abierto |
| Palabra clave: | Fog Remote sensing Boira Teledetecció Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica |
| Sumario: | This paper focuses on exploring ways to improve the performance of LiDAR imagers through fog. One of the known weaknesses of LiDAR technology is the lack of tolerance to adverse environmental conditions, such as the presence of fog, which hampers the future development of LiDAR in several markets. Within this paper, a LiDAR unit is designed and constructed to be able to apply temporal and polarimetric discrimination for detecting the number of signal photons received with detailed control of its temporal and spatial distribution under co-polarized and cross-polarized configurations. The system is evaluated using different experiments in a macro-scale fog chamber under controlled fog conditions. Using the complete digitization of the acquired signals, we analyze the natural light media response, to see that due to its characteristics it could be directly filtered out. Moreover, we confirm that there exists a polarization memory effect, which, by using a polarimetric cross-configuration detector, allows improvement of object detection in point clouds. These results are useful for applications related to computer vision, in fields like autonomous vehicles or outdoor surveillance where many variable types of environmental conditions may be present. |
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