Development of LIDAR for applications in transport

在各种新技术中，光探测与测距是实现态势感知的关键技术之一。该项目旨在开发概念上新的基于激光的技术，专门用于解决交通应用中遇到的挑战，包括自动驾驶汽车和智能城市。该项目的重点是使用多波束方法，其中几个源和探测器一起形成一个组合系统。学生将在实验室中开发一个光学装置，并将测试其使用计算方法提取成像和测距信息的能力。特别是将研究深度学习神经网络的使用，以便将光学数据映射到位置信息上。学生将寻求新的应用领域，并与我们的合作伙伴Dstl合作探索新的方向。

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.