Development of LIDAR for applications in transport

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Light detection and ranging is one of the key technologies that can enable situational awareness in a variety of new technologies. This project aims to develop conceptually new laser-based techniques that are specifically designed to solve challenges encountered in transport applications, including self driving cars and smart cities. The focus of the project is on using multi-beam approaches where several sources and detectors together form a combined system. The student will develop an optical setup in the laboratory, and will test its capability of extracting imaging and ranging information using computational methods. In particular the use of deep learning neural networks will be investigated in order to map optical data onto positional information. The student will seek new application areas and will explore new directions in collaboration with our partner in this CASE conversion, Dstl.