Open World Recognition of Communication Jamming Signals

To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new classes.The network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known dataset.On the one hand,the network is required to have the ability to distinguish whether two samples are from the same class.On the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set testing.During the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known classes.The simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.

Research on Blanket Jamming to Beidou Navigation Signals Based on BOC Modulation

Aiming at the issue of influence of blanket jamming on performances of Beidou navigation signals, through studying Beidou signals based on the BOC modulation technology, establishing a blanket jamming mathematical model, and performing modeling and simulation on multiple jamming technologies, to attain the jamming curves of time domains and frequency domains of Beidou signals, and the correlation curve of the signal-to-jamming rate and the bit error rate under blanket jamming, and thus realizing evaluation on the jamming performance.

Optimal Periodic Pulse Jamming Signal Design for QPSK Systems

The problem of optimal periodic pulse jamming design for a quadrature phase shift keying（QPSK）communication system is investigated.First a closed-form bit-error-rate（BER）of QPSK system under the jamming of pulse signal is derived.Then the asymptotic performance of the derived BER is analyzed as the signal-to-noise ratio（SNR）grows to infinity.In order to maximize the BER of the QPSK system,the optimal parameters of periodic pulse jamming signal,including the duty cycle and signal-tojamming power ratio（SJR）,are found out.Numerical results are presented to verify our analytical results and the optimality of our design.

Sinusoidal FM Fuze's Channel Leak and Its Jamming Mechanism

Aim To get the theory base of designing FM fuze's jamming signal, its jamming mechanism was studied. Methods A sinusoidal FM fuze was analyzed in time domain and frequency domain and the concept of channel leak was presented. Results It was proved that information channel leak exists in FM fuze because of the nonlinear property of the mixer. The jamming signal was designed based on the channel leak and the jamming mechanism was analyzed in detail. Conclusion This kind of jamming signal can jam the sinusoidal FM fuzes effectively just depending on the jamming signal's feature itself. It's different from the traditional jamming way of simulating echo. Though the sinusoidal FM fuze was just analyzed, the principle is applicable to all FM fuzes. At the same time, it may be used as the reference for FM radar and communication countermeasures.

Traffic jam in signalized road network

Traffic jam in large signalized road network presents a complex nature.In order to reveal the jam characteristics,two indexes,SVS(speed of virtual signal) and VOS(velocity of spillover),were proposed respectively.SVS described the propagation of queue within a link while VOS reflected the spillover velocity of vehicle queue.Based on the two indexes,network jam simulation was carried out on a regular signalized road network.The simulation results show that:1) The propagation of traffic congestion on a signalized road network can be classified into two stages:virtual split driven stage and flow rate driven stage.The former stage is characterized by decreasing virtual split while the latter only depends on flow rate; 2) The jam propagation rate and direction are dependent on traffic demand distribution and other network parameters.The direction with higher demand gets more chance to be jammed.Our findings can serve as the basis of the prevention of the formation and propagation of network traffic jam.

Mainlobe jamming suppression via improved BSS method for rotated array radar

This study deals with the problem of mainlobe jamming suppression for rotated array radar.The interference becomes spatially nonstationary while the radar array rotates,which causes the mismatch between the weight and the snapshots and thus the loss of target signal to noise ratio(SNR)of pulse compression.In this paper,we explore the spatial divergence of interference sources and consider the rotated array radar anti-mainlobe jamming problem as a generalized rotated array mixed signal(RAMS)model firstly.Then the corresponding algorithm improved blind source separation(BSS)using the frequency domain of robust principal component analysis(FDRPCA-BSS)is proposed based on the established rotating model.It can eliminate the influence of the rotating parts and address the problem of loss of SNR.Finally,the measured peakto-average power ratio(PAPR)of each separated channel is performed to identify the target echo channel among the separated channels.Simulation results show that the proposed method is practically feasible and can suppress the mainlobe jamming with lower loss of SNR.

On the critical conditions of traffic jams

Traffic wave theory is used to study the critical conditions for traffic jams according to their features. First, the characteristics of traffic wave propagation is analyzed for the simple signal-controlled lane and the critical conditions for oversaturation is established. Then, the basic road is decomposed into a series of one-way links according to its topological characteristics. Based on the decomposition, traffic wave propagation under complex conditions is studied. Three complicated factors are considered to establish the corresponding critical conditions of jam formation, namely, dynamic and insufficient split, channelized section spillover and endogenous traffic flow. The results show that road geometric features, traffic demand structures and signal settings influence the formation and propagation of traffic congestion. These findings can serve as a theoretical basis for future network jam control.

A Coincered Node Based Localization of Jammers in Wireless Sensor Networks

Jammers can awfully interfere with the wireless communications. The transmission and reception of wireless communication is blocked by the jammer. The intruder will place the jammer in a well topological network area and they can easily track the information. It will help them to block the signal transmission and reception. Now, the intention is to track the position of the jammer where it is fixed. The existing methods rely on the indirect measurements and the boundary node to find the jammer’s position which degrades the accuracy of the localization. To improve the efficiency, this paper proposed an efficient method namely Coincered Node Based Localization of jammers to find the position of the jammer with high level of accuracy. The proposed system uses the direct measurements, which is the jammer signal strength. The effectiveness can also be increased by using the coincered node that will stumble across the true position of the jammer. The proposed work is compared with existing methods. Then the proposed mechanism proves better to find the jammer location. The simulation results estimate that the accuracy of the localization achieves better performance than the existing schemes.

基于多维小波特征的有源雷达欺骗干扰识别

针对跟踪工作模式下常见雷达有源欺骗干扰识别问题,通过分析雷达信号和干扰模型,提出一种基于多维小波特征的识别算法。对目标回波多个相干处理间隔中的首个脉冲重复间隔内信号采样累积,构成一维离散序列,利用Mallat算法提取多尺度小波系数,计算不同尺度下小波系数的移位相关系数,并组成特征向量用于分类识别。构建不同参数的信号样本仿真,在信噪比为-5 dB时仍有高于80%的识别正确率。该算法能将距离假目标干扰和距离拖引干扰有效识别,证明了算法的准确性、通用性和严谨性。此外,针对实际情况,可以调整特征向量维度,选择更适合的母小波函数,进一步优化干扰识别效果。

共享信号模式的探测干扰一体化系统设计

为解决传统信息战装备呈现出的模式单一、自适应能力差、资源冗余度高等问题,提出了基于共享信号的探测干扰一体化系统优化方案,从系统结构、工作流程、工作模式和核心模块等方面对探测干扰一体化系统进行了详细设计。梳理了实现一体化系统所存在的科学问题与技术难点,通过分析脉内复合调制和动态避障两类共享波形的性能,验证了两类波形均具备同时探测、干扰的能力,说明了共享信号模式下探测干扰一体化系统的可行性。

单脉冲测角的二维分级主旁瓣干扰联合抑制方法

针对矩形平面阵列天线同时存在主、旁瓣干扰的单脉冲测角问题,该文设计了2维分级自适应单脉冲波束形成算法(TDHJ-ADBF)。TDHJ-ADBF算法将矩形平面阵分为方位维和俯仰维两个正交维度,采用2维分级处理架构:第1级处理在测角维进行,采用低运算量的压缩多重信号分类法对测角维主瓣干扰进行快速识别与方向估计,构造阻塞矩阵滤除主瓣干扰,获得仅含旁瓣干扰和噪声的协方差矩阵,进而对和、差波束方向图进行指向与鉴角曲线联合约束,完成测角维旁瓣干扰抑制与波束形成处理;第2级在非测角维对残留的测角维主瓣干扰进行抑制。通过2维分级处理实现主、旁瓣干扰联合对抗,并保持单脉冲测角的鉴角曲线线性度。仿真结果表明,TDHJ-ADBF算法实现了对主、旁瓣干扰联合抑制,具有高精度的单脉冲测角性能。

对瞬时测频干扰机理的研究

瞬时测频(instantaneous frequency measurement,IFM)接收机是电子侦察中非常重要的测频资源,其结构简单、灵敏度高、侦察频带宽、分辨率高,可以快速测定被测信号的频率,在现代电子战中得到广泛应用。基于IFM微波鉴相器在某一瞬间只能响应一个信号的特性,结合IFM工作原理,研究了一种新的(超过2个信号)对IFM干扰策略,并分析了干扰机理,通过模拟仿真对IFM的干扰效果进行了评估。仿真结果表明:多信号交叠可以对IFM系统产生明显的干扰效果,可以使得其无法测得正确频率,并错误地输出同时到达信号指示。

SAR抗转发式干扰波形设计与优化

为提高合成孔径雷达(synthetic aperture radar,SAR)系统对抗转发式欺骗干扰的性能,提出一种基于非线性调频(non-linear frequency modulation,NLFM)信号的正交波形设计与优化技术,结合自主收发策略来优化波形组,使捷变发射的波形相互正交,从而达到在复杂环境下抑制转发式欺骗干扰的效果。首先,分析SAR系统转发式欺骗干扰的机理、波形捷变发射方法的合理性和有效性,提出利用正交波形设计进行抗干扰的方法;其次,采用S曲线法和分段函数法产生NLFM信号,基于拉格朗日算法,结合遗传算法对NLFM信号的波形组进行了优化设计;最后,通过仿真实验验证了本文方法设计的优化波形组在SAR系统中对抗转发式欺骗干扰的有效性。结果表明:由分段函数法产生NLFM波形后,在合适的干扰转发时延下,采用拉格朗日遗传算法优化NLFM波形的正交性,改善了波形的主瓣宽度和峰值旁瓣比,增强了捷变波形的正交性,提高了波形质量。

基于相位编码波形和非匹配滤波器设计的间歇采样转发干扰抑制方法

间歇采样转发干扰(ISRJ)利用信号欠采样原理和匹配滤波特点,在雷达信号距离维上产生多个数量可控的虚假目标点。根据ISRJ采样函数特点,本文提出一种针对ISRJ的相位编码波形和非匹配滤波器设计方法。在雷达发射信号前,根据干扰的脉冲宽度和重复频率参数,设计适用于抑制ISRJ的非匹配滤波的相位编码信号。在接收到带有干扰的回波后,根据ISRJ采样函数与发射前设计的编码信号,构建抑制ISRJ的非匹配滤波器,降低干扰能量。仿真结果表明,与传统未经处理的相位编码信号相比,所提方法优化设计的信号表现出更好的抗干扰能力。

分布式间歇采样转发信号对机载干涉仪参数测量影响分析

针对反机载干涉仪侦察场景,该文提出一种基于间歇采样转发技术生成分布式信号对干涉仪参数测量施加干扰的方法。辐射源与转发干扰机分布部署构成干扰系统,转发干扰机对辐射源脉冲信号进行间歇采样并向干涉仪转发,转发信号与辐射源信号准同步到达干涉仪,实现对干涉仪空域参数和时域参数的同时干扰。对于机载干涉仪运动过程中与干扰系统发生的位置关系变化,给出信号准同步约束并构建分布式信号叠加模型。然后针对干涉仪体制对脉冲空域和时域参数的测量机理,分析分布式信号实施干扰的原理,并分析信号参数对干扰效果的影响,进而提出分布式信号设计原则。仿真实验和暗室实验结果表明,该文所提出分布式波形可有效扰乱干涉仪对信号到达方位角、脉宽和脉冲重复周期等空时域参数的正确测量。

通信干扰信号分类识别方法综述

通信干扰信号的分类识别作为通信抗干扰的前提和基础,被广泛运用于无线通信和通信电子战等诸多领域。从通信干扰信号分类识别的基本原理出发,将分类识别方法分为基于人工特征提取(Manual Feature Extraction,MFE)和自动特征学习(Automatic Feature Learning,AFL)两大类进行介绍。系统阐述了两类方法的区别,并对比分析了不同方法的特点和性能。最后,分析了该领域面临的挑战,并对未来的研究方向进行了展望。

基于信号变分分解的无线电引信抗干扰方法

脉冲多普勒引信在受到扫频式干扰时,引信接收机信道被干扰信号饱和从而导致引信出现早炸或瞎火。脉冲多普勒引信通过波形设计及多维度特征识别可以避免因干扰信号而错误启动,但如何在扫频式干扰压制下检测真实目标仍是一个难题。针对上述问题,建立了扫频式干扰作用下脉冲多普勒引信中频信号模型,并提出了基于信号变分分解的引信抗扫频式干扰方法。所提方法利用全变分正则化将中频信号分解为脉冲、低频正弦波和高频噪声3个分量,保留并处理对应目标回波信号的脉冲分量即可检测真实目标。通过仿真验证了方法的有效性,结果表明:所提方法在0~20 dB的干信比条件下仍能有效分离目标回波及干扰信号,大大提高了脉冲多普勒引信在扫频式干扰作用下的目标检测能力。

压制式干扰信号对卫星导航接收机的影响研究

针对缺少不同样式、带宽和频偏参数压制式干扰信号对卫星导航接收机作用效果的全面分析,文中基于卫星导航接收机跟踪门限和码跟踪误差,采用仿真方法分析了不同干扰参数信号对跟踪过程的影响,分析出BPSK和QPSK调制信号的干扰样式效果较好,且最佳干扰带宽、中心频率并不一定等于导航信号带宽和中心频率。文中通过搭建室外、室内实验环境,进一步验证了不同干扰信号参数对卫星导航接收机的影响,其结果与仿真结论基本一致。

重频组合脉冲干扰对雷达信号分选的影响分析

为提高雷达信号主动抗分选能力,从削弱分选算法对脉冲重复间隔分选性能的角度出发,分析了直方图法、PRI变换法的算法特征;在一定约束条件下合理设计脉冲干扰信号,并进行仿真验证.仿真结果表明,干扰信号可以改变分选算法对真实雷达重频的统计属性,使侦察系统产生错误或虚假的雷达信号重频,从而实现对高价值目标的电磁防护.

基于微分约束的改进自适应多波束抗干扰算法

卫星导航抗干扰技术作为导航接收机中最重要的部分之一,将直接决定导航定位的可靠性和准确性。自适应多波束导航抗干扰技术作为目前抗干扰性能最高的抗干扰技术,其不仅可以对干扰方向进行抑制,还可以对卫星信号方向产生增益,为导航信号提供有效保护。但自适应多波束抗干扰算法需要实时获取卫星信号相对天线阵面的入射角信息,在实际工程应用中,考虑到惯导的姿态测量误差以及载体平台的运动,获取的入射角信息存在一定的偏差,滤波后会引起信号损失。针对这个问题,提出一种基于微分约束的改进自适应多波束抗干扰算法。该方法以LCMV准则为目标函数,通过在卫星信号入射方向和干扰方向上增加一定角度范围进行约束,削弱入射角度偏差引起的信号损失。仿真结果表明,该方法在一定的角度偏差范围内可有效保护卫星信号并抑制干扰信号,从而提高抗干扰性能。