【作者】 杨凡；

【导师】 罗锴； 陈达；

【作者基本信息】 华中科技大学 ， 信息与通信工程， 2024， 硕士

【摘要】 雷达与通信一体化系统(Integrated Radar and Communications System,IRCS)旨在高效利用频谱资源,实现雷达与通信功能的有机融合,对提高作战效能、推动通信网络的创新感知业务发展具有重要意义。在诸多一体化路径中,一体化波形因融合程度最高而成为研究重点。然而,雷达波形与通信波形存在本质需求差异,系统接收端信号处理也会随着一体化波形的应用而面临新的挑战。本文针对上述问题,主要研究基于线性调频(Linear Frequency Modulation,LFM)信号的一体化波形设计方案,通过设计合适的优化策略实现雷达性能与通信性能的有效权衡,同时为雷达通信一体化系统接收端信号处理提供有效解决方案。首先,本文提出一种在LFM信号中嵌入正交振幅调制(Quadrature Amplitude Modulation,QAM)符号的LFM-QAM一体化信号模型,分析LFM-QAM信号在雷达与通信系统关键性能评价指标方面的表现,仿真结果表明,LFM-QAM信号在探测性能方面,相比LFM信号出现了检测性能下降、模糊函数旁瓣随机波动、峰均功率比提高;在通信性能方面,脉冲体制导致其通信速率较低。其次,本文研究了基于LFM-QAM的一体化波形优化设计策略。针对LFM-QAM信号的能量泄露,提出了一种改进的脉冲调制结构。基于LFM-QAM信号模糊函数统计特性的定量分析,提出基于概率整形的模糊函数方差优化模型,并采用障碍函数内点法求解。通过进一步调整星座图四阶原点矩的优化目标,实现了LFM-QAM波形在探测性能、可达信息速率、误码率三者间的有效权衡。最后,本文研究了一体化波形优化设计之后的接收端信号处理问题。针对雷达接收端的距离旁瓣调制问题,分析了传统解决方案的原理与局限性,提出基于Transformer深度学习架构的网络模型,实现了接收滤波器的优化设计。针对通信端的时间同步问题,提出一种基于改进脉冲调制结构的同步方案,通过仿真验证了所提方法的有效性。更多还原

【Abstract】 Integrated radar and communications system(IRCS)is aimed at efficiently utilizing spectrum resources and achieving a seamless integration of radar and communications functions,which are crucial for enhancing combat effectiveness and driving the development of sensing services in the next generation of wireless communication.Among various integration approaches,integrated waveform design has been identified as a focal point due to its high degree of fusion.However,fundamental challenges are presented by the inherent differences between radar and communications waveforms,and new challenges are faced by the system’s signal processing at the receiving end with the application of integrated waveforms.In this dissertation,these issues are addressed through a focus on integrated waveform design based on linear frequency modulation(LFM)signals.Effective balancing of radar and communications performance is achieved through appropriate optimization strategies,and viable solutions for signal processing at the receiving end of integrated radar and communications systems are provided.First,an integrated signal model of LFM-QAM,in which quadrature amplitude modulation(QAM)symbols are embedded into LFM signals,is proposed.The performance of the LFM-QAM signal in terms of key performance indicators for radar and communications systems is analyzed.Simulation results shown that,in terms of detection performance,the LFM-QAM signal experiences a reduction in detection capabilities,random fluctuations in the sidelobes of the ambiguity function,and an increase in the peakto-average power ratio compared to LFM signals.In terms of communications performance,the pulse regime results in a lower communications rate.Second,an optimization design strategy of integrated waveform based on LFM-QAM is investigated in this dissertation.In response to the energy leakage of the LFM-QAM signal,an improved pulse modulation structure has been proposed.A variance optimization model of the ambiguity function based on probability shaping,which is based on the quantitative analysis of the statistical characteristics of the LFM-QAM signal’s ambiguity function,has been introduced and solved using the barrier function interior-point method.By further adjusting the optimization objective of the fourth-order origin moment of the constellation diagram,an effective balance among detection performance,achievable information rate,and symbol error rate of the LFM-QAM waveform has been achieved.Finally,the received signal processing following the optimization design of integrated waveforms is investigated in this dissertation.In response to the issues of range sidelobe modulation at the radar receiving end,the limitations of traditional solutions have been analyzed,and a deep learning architecture based on the Transformer has been proposed to design receiver filter.Experimental results indicate that the proposed network model exhibits good performance.For the time synchronization at the communications receiving end,a synchronization scheme based on the improved pulse modulation structure is proposed,and the effectiveness of the proposed scheme is verified through simulation.更多还原