Multi Static RF Sensing with Active and Passive Nodes

近年来，由于可在协调网络中运行的可重新编程软件定义解决方案的进步，雷达系统得到了显著发展。明显的趋势是，从单一的大型单基地雷达系统平台转向一系列更小、更灵活的平台，使用多基地传感和协调获得的信息。关于如何利用有源和无源雷达传感器的组合，已经完成了很少的工作，这项研究的目的是在这种传感中推动新的想法，以帮助解决这一挑战中的问题。通过你的研究，你将发展实验雷达测量、信号处理和算法设计、数据分析和有效沟通的技能。候选人将对在主动和被动模式组合中利用多个雷达节点的复杂挑战进行创新研究。这些拟议的雷达网络具有在复杂情况下运行的巨大潜力，并且仍然可以探测到具有挑战性的目标。博士生将有机会1)使用现有系统并为雷达网络开发新的硬件2)对具有挑战性的目标（如小型无人机）进行实验和3)分析收集的数据，以优化感兴趣目标的检测，跟踪和分类。

Radar systems have developed significantly over recent years due to advances in re-programmable software defined solutions that can operate in co-ordinated networks. The clear trend is to move away from single large platforms with a monostatic radar system to a series of smaller more agile platforms, using multistatic sensing and co-ordinating the information obtained. Little work has been completed into how to utilize a combination of active and passive radar sensors and this research will aim to push new ideas within this sensing to help solve problems in this challenge. Through your research, you will develop skills in experimental radar measurements, signal processing and algorithm design, data analysis and effective communication.The candidate will conduct innovative research on the complex challenge of utilizing multiple radar nodes in a combination of active and passive modes. These proposed radar networks have significant potential to operate in complex scenarios and still detect challenging targets. The PhD student will have the opportunity to 1) Use existing systems and develop new hardware for a radar network 2) Perform experiments with challenging targets (such as small drones) and 3) Analyse the data gathered in order to optimise the detect, track and classification of the targets of interest.