【作者】 李浩；

【导师】 张伟；

【作者基本信息】 电子科技大学 ， 电子与通信工程（专业学位）， 2021， 硕士

【摘要】 经典的雷达抗干扰技术利用目标与干扰信号在时域、频域或空域的差异,通过脉冲压缩、频域滤波或旁瓣对消方式进行抑制。随着DRFM(数字射频存储)技术的快速发展,多种新型相干干扰不断涌现,很难用一种方式抑制不同的干扰。基于对新型干扰的认知,研究针对性的干扰抑制算法,从而提高雷达的抗干扰检测性能,是雷达抗干扰技术的研究热点。本文针对间歇采样转发干扰以及灵巧噪声干扰,研究了干扰认知方法,采用基于干扰重构对消和基于变换滤波的抗干扰方法对两类干扰进行有效抑制,并设计实现了基于干扰认知的雷达抗干扰仿真系统。主要的工作内容概述如下。(1)对基于DRFM的间歇采样转发干扰和灵巧噪声干扰进行分析和建模,在此基础上对含有干扰的雷达回波进行基于恒虚警的检测与参数粗估计。检测干扰后,采用深度学习方法对间歇采样转发干扰、灵巧噪声干扰和其它类型干扰进行识别,识别率达到99.47%,为准确的干扰认知提供支持。(2)现有的间歇采样转发干扰参数估计主要基于Hilbert-Huang变换,存在干扰采样周期估计精度不足问题,本文采用基于模糊函数与HHT进行联合估计方法改善了对干扰的认知。在对干扰参数进行准确估计后进行重构对消干扰,相比HHT方法JSR可以降低3到6dB。(3)针对灵巧噪声干扰同时含有相干性和随机性的特点,首先对干扰通过差拍处理与频域滤波进行预处理,能够消除部分干扰信号。再通过获取干扰与雷达发射信号先验信息并在Fr FT域进行窄带滤波,以消除剩余干扰。脉冲压缩处理显示,上述处理比直接Fr FT域滤波的干扰信号形成的波峰小5到8dB。(4)将上述干扰信号的产生、检测、识别与抑制方法进行集成,通过在Matlab软件APP Designer平台开发雷达抗干扰仿真软件界面,设计了干扰信号仿真、数据处理与识别和干扰抑制三个模块,可方便灵活的进行干扰抑制仿真测试。更多还原

【Abstract】 The classical radar jamming suppression technology uses the difference between the target and the jamming signal in time domain,frequency domain or spatial domain to suppress by pulse compression,frequency domain filtering or sidelobe cancellation.With the rapid development of DRFM(Digital Radio Frequency Memory)technology,a variety of new coherent interferences are emerging.It is difficult to suppress different interferences in one way.Based on the recognition of the new jamming,it is a research hotspot of radar jamming suppression technology to study the targeted jamming suppression algorithm,so as to improve the jamming suppression detection performance of radar.Aiming at the intermittent sampling and forwarding jamming and smart noise jamming,this paper studies the jamming cognitive method,adopts the jamming suppression method based on jamming reconstruction cancellation and transform filtering to effectively suppress the two kinds of jamming,and designs and realizes the radar jamming simulation system based on jamming cognitive.The main work is summarized as follows.(1)Based on the analysis and modeling of intermittent sampling repeater jamming and smart noise jamming based on DRFM,CFAR based detection and parameter rough estimation of radar echo with jamming are carried out.After interference detection,deep learning method is used to recognize intermittent sampling and forwarding interference,smart noise interference and other types of interference.The recognition rate reaches99.26%,which provides support for accurate interference cognition.(2)The existing intermittent sampling repeater interference parameter estimation is mainly based on Hilbert Huang transform,which has the problem of insufficient accuracy of interference sampling period estimation.In this paper,the joint estimation method based on fuzzy function and HHT is used to improve the cognition of interference.Compared with HHT method,JSR can be reduced by 3 to 6dB.(3)According to the characteristics of both coherence and randomness of smart noise interference,firstly,the interference is preprocessed by beat processing and frequency domain filtering,which can eliminate part of the interference signal.Then,by acquiring the prior information of jamming and radar transmitting signal,the residual jamming is eliminated by narrowband filtering in FRFT domain.In the results of pulse compression processing,after the improvement of beat pre-processing,it shows that the residual peak formed by the above processing is 5 to 8 dB smaller than that of the interference signal filtered directly in FRFT domain.(4)The generation,detection,identification and suppression methods of the above jamming signal are integrated.Through the development of radar jamming suppression simulation software interface in MATLAB software app designer platform,three modules of jamming signal simulation,data processing and identification and jamming suppression are designed,which are convenient and flexible for jamming suppression simulation test.更多还原