An approach for predicting digital material consumption in electronic warfare

Electronic warfare is a modern combat mode,in which predicting digital material consumption is a key for material requirements planning(MRP).In this paper,we introduce an insensitive loss function(ε) and propose a ε-SVR-based prediction approach.First,we quantify values of influencing factors of digital equipments in electronic warfare and a small-sample data on real consumption to form a real combat data set,and preprocess it to construct the sample space.Subsequently,we establish the ε-SVR-based prediction model based on "wartime influencing factors-material consumption" and perform model training.In case study,we give 8 historical battle events with battle damage data and predict 3 representative kinds of digital materials by using the proposed approach.The results illustrate its higher accuracy and more convenience compared with other current approaches.Taking data acquisition controller prediction as an example,our model has better prediction performance(RMSE=0.575 7,MAPE(%)=12.037 6 and R^2=0.996 0) compared with BP neural network model(RMSE=1.272 9,MAPE(%)=23.577 5 and R^2=0.980 3) and GM(1,1) model(RMSE=2.095 0,MAPE(%)=24.188 0 and R^2=0.946 6).The fact shows that the approach can be used to support decision-making for MRP in electronic warfare.

Waveform design for radar and extended target in the environment of electronic warfare

Transmit waveform optimization is critical to radar system performance. There have been a fruit of achievements about waveform design in recent years. However, most of the existing methods are based on the assumption that radar is smart and the target is dumb, which is not always reasonable in the modern electronic warfare. This paper focuses on the waveform design for radar and the extended target in the environment of electronic warfare. Three different countermeasure models between smart radar and dumb target, smart target and dumb radar, smart radar and smart target are proposed. Taking the signal-to-interferenceplus-noise ratio(SINR) as the metric, optimized waveforms for the first two scenarios are achieved by the general water-filling method in the presence of clutter. For the last case, the equilibrium between smart radar and smart target in the presence of clutter is given mathematically and the optimized solution is achieved through a novel two-step water-filling method on the basis of minmax theory. Simulation results under different power constraints show the power allocation strategies of radar and target and the output SINRs are analyzed.

Electronic warfare in the optical band:Main features,examples and selected measurement data

The paper presents the possibilities of,and methods for,acquiring,analysing and processing optical signals in order to recognise,identify and counteract threats on the contemporary battleground.The main ways electronic warfare is waged in the optical band of the electromagnetic wave spectrum have been formulated,including the acquisition of optical emitter signatures,as well as ultraviolet(UV)and thermal(IR)signatures.The physical parameters and values describing the emission of laser radiation are discussed,including their importance in terms of creating optical signatures.Moreover,it has been shown that in the transformation of optical signals into signatures,only their spectral and temporal parameters can be applied.This was confirmed in experimental part of the paper,which includes our own measurements of spectral and temporal emission characteristics for three types of binocular laser rangefinders.It has been further shown that through simple registration and quick analysis involving comparison of emission time parameters in the case of UV signatures in“solar-blind”band,various events can be identified quickly and faultlessly.The same is true for IR signatures,where the amplitudes of the recorded signal for several wavelengths are compared.This was confirmed experimentally for UV signatures by registering and then analyzing signals from several events during military exercises at a training ground,namely Rocket Propelled Grenade(RPG)launches and explosions after hitting targets,trinitrotoluene(TNT)explosions,firing armour-piercing,fin-stabilised,discarding sabots(APFSDS)or high explosive(HE)projectiles.The final section describes a proposed model database of emitters,created as a result of analysing and transforming the recorded signals into optical signatures.

A joint optimization algorithm for focused energy delivery in precision electronic warfare

Focused energy delivery(FED) is a technique that can precisely bring energy to the specific region,which arouses wide attention in precision electronic warfare(PREW).This paper first proposes a joint optimization model with respect to the locations of the array and the transmitted signals to improve the performance of FED.As the problem is nonconvex and NP-hard,particle swarm optimization(PSO) is adopted to solve the locations of the array,while designing the transmitted signals under a feasible array is considered as a unimodular quadratic program(UQP) subproblem to calculate the fitness criterion of PSO.In the PSO-UQP framework established,two methods are presented for the UQP subproblem,which are more efficient and more accurate respectively than previous works.Furthermore,a threshold value is set in the framework to determine which method to adopt to take full advantages of the methods above.Meanwhile,we obtain the maximum localization error that FED can tolerate,which is significant for implementing FED in practice.Simulation results are provided to demonstrate the effectiveness of the joint optimization algorithm,and the correctness of the maximum localization error derived.

高对抗强博弈场景下雷达波形设计思路

未来陆域突击作战中高对抗强博弈场景使得雷达与目标间博弈日趋激烈,雷达波形作为雷达装备的核心和基础特征,将是提高雷达对目标检测性能的关键因素。该文首先梳理高对抗强博弈场景下的军事需求和发展现状,然后从波形产生与处理、目标和环境信息参数化建模、波形博弈方法等方面展开讨论,可为雷达在复杂电磁环境下如何提升装备作战效能提供设计参考。

美军可重构电子战系统发展现状分析

由于电磁环境日益复杂,以及新目标不断涌现,为了快速有效应对新威胁,美军提出了电子战可重构相关的系列新思路、新技术,并加速推动其验证与应用,特别是提出了结合人工智能新技术围绕新目标对象进行电子战能力快速生成,实现任务、软件、硬件的快速更新。通过从美军条令论证、技术验证、装备应用等角度进行分析,得出了结合平台化、无人化、智能化、网络化的电子战系统可重构发展路线启示。

基于威胁机制-双重深度Q网络的多功能雷达认知干扰决策

针对传统深度Q网络(deep Q network,DQN)在雷达认知干扰决策中容易产生经验遗忘,从而重复执行错误决策的问题,本文提出了一种基于威胁机制双重深度Q网络(threat warning mechanism-double DQN,TW-DDQN)的认知干扰决策方法,该机制包含威胁网络和经验回放2种机制。为了验证算法的有效性,在考虑多功能雷达(multifunctional radar,MFR)工作状态与干扰样式之间的关联性的前提下,搭建了基于认知电子战的仿真环境,分析了雷达与干扰机之间的对抗博弈过程,并且在使用TW-DDQN进行训练的过程中,讨论了威胁半径与威胁步长参数的不同对训练过程的影响。仿真实验结果表明,干扰机通过自主学习成功与雷达进行了长时间的博弈,有80%的概率成功突防,训练效果明显优于传统DQN和优先经验回放DDQN(prioritized experience replay-DDQN,PER-DDQN)。

美军防区内防空压制装备作战运用研究

当前,美军正借鉴俄乌冲突实战经验,大力开发防区内防空压制作战装备,并通过作战试验检验开发其战术战法,预计美军将在2027年前形成体系化的防区内防空压制作战能力。分析了美军开发防区内防空压制电子干扰装备的动因,对美军典型防区内防空压制作战装备进行了介绍,归纳了美军防区内防空压制作战装备体系的特点,最后总结了美军防区内防空压制作战装备的战法。

俄罗斯非动能反卫星能力发展分析

俄罗斯面临美国太空军事化带来的严重威胁,不断加大非动能反卫星系统的研制和部署的步伐。文章回顾了近年来俄罗斯非动能反卫星能力现状,分析了其发展特点及未来发展趋势,并提出相关建议。

美军认知电子战关键技术发展方向分析

美军认知电子战相关概念发展迅速,也开展了较多的项目研究。为分析其关键技术发展现状并研判其未来发展趋势,从美高校、智库、军事科研机构、厂商4个角度,通过研究论文、报告等公开文献,对美军认知电子战关键技术发展情况,特别是其在机器学习、人工智能方面的探索进行了深入的分析,对美军认知电子战技术领域研究方向、潜在难题及对应的关键技术思路进行了较为全面的梳理,并从数据、模型、平台、应用等方面给出了启示。

舰载电子战飞机与无人机协同作战视图研究

为更加高效帮助航母编队指挥所和指挥员精准判断战场态势,进而作出最佳决策,从战术运用角度分析未来舰载电子战飞机与无人机协同实施电子进攻行动的优势,通过借鉴美军DoDAF(department of defense architecture framework)体系结构框架设计思路,启发构建“五视图体系”,用以清晰呈现各参战平台在重要时间节点的具体行动及内在联系。该研究对于未来进一步优化我航母编队遂行作战任务流程具有较强的现实意义和理论价值。

基于多域特征的多雷达信号自动识别方法

为解决复杂电磁环境中多台雷达在相似的频段上同时发射各自的信号,导致侦察接收信号在时域和频域上重叠的问题,提出一种低信噪比(SNR)下自动调制识别(MR)方法。通过接收脉冲间列快速傅里叶变换(FFT)将接收信号的能量集中在各自的多普勒频率上,以达到分离多个截获信号的目的;将每个信号的Wigner-Ville分布(WVD)和模糊函数(AF)作为一幅图像的2层同时发送到训练后的残差神经网络(ResNet),以解决某些类型的信号仅采用单一时频分布时识别精度低的问题。理论分析和仿真结果表明:所提方法不仅能有效分离时域和频域重叠的多个雷达信号,而且能在SNR为-10 dB的条件下准确识别其调制模式。

美陆军网络与电子战融合发展分析

美陆军网络空间作战与电子战在作战条令、技术和装备方面都发展较快,但缺少全方位理解和关联关系的深入分析。对其网络建设与电子战发展现状进行深度分析发现,美陆军以数据融合、网络协同等作战需求为牵引,以战略与指南手册为先手,以能力集和项目方式推动关键技术的突破,结合统一、高安全的战术网络发展路线,规划电子战装备并不断更新迭代,支撑网络空间作战与电子战的加速融合。对上述发现进行提炼,得出美陆军新网络建设、新基础支撑、新技术转化、新能力塑造、新战法融合、新装备集成的网络与电子战融合发展趋势与启示。

电子战无人机反向交叉眼干扰研究

针对机载两源反向交叉眼干扰在实际应用中遇到的参数容限严苛和干信比需求高的问题,提出了一种创新的解决方案,即利用电子战无人机(EWUAV)搭载反向交叉眼干扰机对敌方制导雷达进行抵近干扰。首先,建立了EWUAV反向交叉眼干扰模型,通过深入分析该模型,揭示出机载两源反向交叉眼干扰模型实则是其一个特例;其次,在确定干扰有效性方面,设定了一个明确的指标:当视在假目标的爆炸范围不触及被保护平台的物理边界时,即认为干扰达到预期效果。此外,文中还详细推导了雷达指示角,创新性地将其参数分为几何与电参数两类进行深入分析;最后,通过一系列仿真实验,充分证明了所提方法不仅有效,而且在参数容限和干信比需求方面表现更为宽松和优越。

人工智能在美国陆军电子战发展应用研究

伴随着人工智能等智能化技术的快速发展以及美军“电磁频谱作战”概念的提出,美军电子战呈现出智能化发展趋势。美国陆军积极推动电子战作战理念向电磁频谱作战发展演变,同时广泛开展智能化电子战技术和装备研究。通过文献调研、碎片化信息还原和比较分析法,从智能化视角分析美国陆军电子战作战理念发展演变,研究美国陆军典型的人工智能电子战项目内容及发展现状,分析研判美国陆军未来电子战及电磁频谱作战充分依托既有作战平台、探索与网络战一体化运用、大力推动智能化电子战系统装备建设等发展趋势,有一定的启示和借鉴意义。

地形遮蔽下的电磁波绕射效应对机载电子战影响

针对机载电子战中经常遇到的地形遮蔽问题,定量分析了遮蔽条件下电磁波绕射效应对机载电子战设备的影响。首先基于传统刃形单峰绕射模型提出了在地球曲率下山峰绕射高度的计算方法;然后基于Picquenard刃形多峰绕射模型提出了地球曲率下的主峰迭代搜索算法;最后利用构建的电磁波绕射模型,提出了机载电子战在地形遮蔽情况下的对抗策略。将算法嵌入模型后,通过比对仿真结果与真实试验数据,表明所提算法可适用于计算地形遮蔽对机载电子战设备的影响。

雷达对抗技术研究综述与智能反干扰展望

电磁频谱的争夺是未来信息化战场至关重要的博弈对抗,为了应对更加灵巧和智能化的电子干扰,雷达也必须要发展智能化的反干扰技术。围绕当前雷达反干扰技术发展现状,将雷达反干扰技术框架分解为被动干扰抑制、主动干扰抑制和认知反干扰3个主要模块,从基础原理、实现逻辑、性能表现等方面对近几年的代表性文献进行了归纳总结。在此基础上,引入了干扰记忆诱导的智能化反干扰概念,丰富了雷达反干扰智能化内涵。并进一步分析了未来该领域的技术需求、应对场景以及发展趋势,为后续的反干扰技术智能化发展提供参考和依据。

基于可视图深度学习的雷达天线扫描样式识别

针对相控阵雷达扫描信号难识别的问题,提出一种基于可视图深度学习的雷达扫描样式识别方法。首先,分析了7种常见的雷达天线扫描样式。然后,将接收到的天线主瓣照射幅度与脉冲到达时间之间的变化趋势转换为可视图矩阵。最后,构建深度网络模型,验证扫描样式识别的效果。试验结果表明,基于可视图深度学习的雷达扫描样式识别方法对7种扫描样式的整体识别准确率在90%以上,并对低信噪比的信号有很好的处理适应性。

具有认知偏差的雷达对抗建模方法

认知偏差是认知电子战中的客观存在。基于动态博弈方法,针对认知雷达对抗过程中因不完整信息和测量误差导致的认知偏差,研究雷达对抗建模方法:以雷达抗干扰改善因子和干扰机干扰效益因子计算博弈双方的效益,采用精炼贝叶斯均衡建立动态雷达对抗模型,分析认知偏差造成的影响。仿真实验结果证明了所提方法的有效性。

舷外有源诱饵及其对抗技术发展综述

随着反舰导弹抗干扰技术发展和性能提升,传统的平台内舰载干扰技术已不足以充分抵御各种海战威胁,因此舷外有源诱饵作为一种具有组网能力的平台外干扰方式备受各国海军的重视。文中首先介绍了舷外有源诱饵的干扰机理、工作特点,分析了舰船防御体系采用舷外有源诱饵的干扰策略,论证了舷外有源干扰的有效性;然后,在此基础上,阐明了国外舷外有源诱饵装备的发展情况和技术特征;最后,针对新型反舰导弹导引头的抗舷外干扰措施,分析了可以采用的对抗手段。研究内容对舷外有源诱饵及其对抗技术进行了全面的阐述,可为后续舷外干扰产品设计和导引头抗干扰技术研究提供支撑。