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Signal Processing and Novel Technologies in Radar Systems

Signal Processing and Novel Technologies in Radar Systems
雷达系统中的信号处理和新技术
批准号:
2435933
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --

项目摘要

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中文摘要
翻译
雷达和通信技术运行在相同的频率上,使得每个系统都容易受到彼此的干扰,导致性能下降。目前减轻干扰的方法对雷达系统的特性有限制,这可能会限制它们在所需环境中工作的适宜性[1]。在过去的十年里,人们研究了一种新的方法,其中将雷达和通信合并到同一平台中,创建了一个双功能雷达通信系统(DFRC)。DFRC系统可以利用雷达结构和雷达脉冲的调制,以便在不影响雷达性能的情况下进行通信[2]。通过集成传统上独立的系统的功能,可以降低成本和功耗,并更有效地管理系统。然而,关于这一新技术,仍有许多问题需要解决。必须开发一个理论框架来优化双功能系统,以便在不损害雷达功能的情况下实现快速数据传输。现有的传输波形被优化为发射它们的系统的单一功能,因此双功能系统的波形需要新的设计。目前的研究没有研究在通信系统中利用雷达相长干扰的潜力。机器学习为雷达和通信系统的频谱共享提供了一种开发复杂数学模型的替代方法。为了实现这项技术的部署,研究必须以使用真实硬件的实验验证为基础。Ratnarajah教授概述的博士项目提供了研究机会,并为克服这些挑战做出了有意义的贡献。
英文摘要
Radar and communication technologies operating across the same frequencies leave each system susceptible tointerference from the other, resulting in performance degradation. Current approaches to mitigating interferenceplace restrictions on the characteristics of the radar system, which may limit their suitability to operate in a desired environment [1].Over the past decade a novel approach has being examined in which radar and communications are incorporatedinto the same platform, creating a dual-function radar communication system (DFRC). The radar architectureand modulation of radar pulses can be exploited by the DFRC system in order to communicate without impactingradar performance [2]. By integrating the functionality of traditionally separate systems, cost and power consumption can be reduced and the systems more efficiently managed.However, there are many questions concerning this novel technology that must be addressed. A theoretical framework must be developed for optimising the dual-function system to facilitate fast data transfer without compromise of radar functionality. Existing transmission waveforms are optimised to the single-function of the systememitting them, so the waveform of a dual-function system requires a novel design. Current research does notexamine the potential for radar constructive interference to be exploited in communication systems. Machinelearning offers an alternative approach to the development of complex mathematical models for spectrum sharing of radar and communications systems. For the deployment of this technology to be realised the research mustbe underpinned by experimental verification using real hardware.The PhD project outlined by Professor Ratnarajah offers the opportunity to research and provide a meaningfulcontribution to overcoming these challenges.
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