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.

The Upstream ＂Strong Signals＂ of the Water Vapor Transport over the Tibetan Plateau during a Heavy Rainfall Event in the Yangtze River Basin

A heavy rainfall event that occurred over the middle and lower reaches of the Yangtze River Basin （YRB） during July 11-13 2000 is explored in this study. The potential/stream function is used to analyze the upstream ＂strong signals＂ of the water vapor transport in the Tibetan Plateau （TP）. The studied time period covers from 2000 LST 5 July to 2000 LST 15 July （temporal resolution： 6 hours）. By analyzing the three-dimensional structure of the water vapor flux, vorticity and divergence prior to and during the heavy rainfall event, the upstream ＂strong signals＂ related to this heavy rainfall event are revealed. A strong correlation exists between the heavy rainfall event in the YRB and the convective clouds over the TE The ＂convergence zone＂ of the water vapor transport is also identified, based on correlation analysis of the water vapor flux two days and one day prior to, and on the day of, the heavy rainfall. And this ＂convergence zone＂ coincides with the migration of the maximum rainfall over the YRB. This specific coupled structure actually plays a key role in generating heavy rainfall over the YRB. The eastward movement of the coupled system with a divergence]convergence center of the potential function at the upper/lower level resembles the spatiotemporal evolution of the heavy rainfall event over the YRB. These upstream ＂strong signals＂ are clearly traced in this study through analyzing the three-dimensional structure of the potential/stream function of upstream water vapor transport.

Loss of the vitamin D receptor in human breast and prostate cancers strongly induces cell apoptosis through downregulation of Wnt/β-catenin signaling

Vitamin D co-regulates cell proliferation, differentiation and apoptosis in numerous tissues, including cancers. The known anti-proliferative and pro-apoptotic actions of the active metabolite of vitamin D, 1,25-dihydroxy-vitamin D [1,25（OH）2D] are mediated through binding to the vitamin D receptor （VDR）. Here, we report on the unexpected finding that stable knockdown of VDR expression in the human breast and prostate cancer cell lines, MDA-MB-231 and PC3, strongly induces cell apoptosis and inhibits cell proliferation in vitro. Implantation of these VDR knockdown cells into the mammary fat pad （MDA-MB-231）, subcutaneously （PC3） or intra-tibially （both cell lines） in immune-incompetent nude mice resulted in reduced tumor growth associated with increased apoptosis and reduced cell proliferation compared with controls. These growth-retarding effects of VDR knockdown occur in the presence and absence of vitamin D and are independent of whether cells were grown in bone or soft tissues. Transcriptome analysis of VDR knockdown and non-target control cell lines demonstrated that loss of the VDR was associated with significant attenuation in the Wnt/0-catenin signaling pathway. In particular, cytoplasmic and nuclear β-catenin protein levels were reduced with a corresponding downregulation of downstream genes such as Axin2, Cyclin D1, interleukin-6 （IL-6）, and IL-8. Stabilization of 0-catenin using the GSK-3β inhibitor BIO partly reversed the growth-retarding effects of VDR knockdown. Our results indicate that the unliganded VDR possesses hitherto unknown functions to promote breast and prostate cancer growth, which appear to be operational not only within but also outside the bone environment. These novel functions contrast with the known anti-proliferative nuclear actions of the liganded VDR and may represent targets for new diagnostic and therapeutic approaches in breast and prostate cancer.

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.

A novel SINR and mutual information based radar jamming technique

The improvements of anti-jamming performance of modern radar seeker are great threats to military targets. To protect the target from detection and estimation, the novel signal-to-interference-plus-noise ratio(SINR)-based and mutual information(MI)-based jamming design techniques were proposed. To interfere with the target detection, the jamming was designed to minimize the SINR of the radar seeker. To impair the estimation performance, the mutual information between the radar echo and the random target impulse response was used as the criterion. The spectral of optimal jamming under the two criteria were achieved with the power constraints. Simulation results show the effectiveness of the jamming techniques. SINR and MI of the SINR-based jamming, the MI-based jamming as well as the predefined jamming under the same power constraints were compared. Furthermore, the probability of detection and minimum mean-square error(MMSE) were also utilized to validate the jamming performance. Under the jamming power constraint of 1 W, the relative decrease of the probability of detection using SINR-based optimal jamming is about 47%, and the relative increase of MMSE using MI-based optimal jamming is about 8%. Besides, two useful jamming design principles are concluded which can be used in limited jamming power situations.

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 STRONG SIGNALS OF MONTHLY PRECIPITATION ANOMALIES IN EARLY RAINING SEASON OF GUANGDONG AND CONCEPTUAL MODELS OF PREDICTION

Reanalysis data from NCEP/NCAR are used to systematically study preceding signals of monthly precipitation anomalies in the early raining season of Guangdong province, from the viewpoints of 500-hPa geopotential height field, outgoing longwave radiation (OLR) field, sea surface temperature (SST) and fourteen indexes of general circulation depicting atmosphere activity at high, middle and low latitutes. Being multiple tools of information, a number of conceptual models are formulated that are useful for prediction of the magnitude of monthly precipitation (drought, flood and normal conditionss).

Sending Strong Signals

Chinese optical fiber maker is becoming a major player in global markets By Yu Nanfiber was invented in 1970, a breakthrough innovation that changed the world. Six years later, the first optical fiber in China was installed by the FiberHome Technol- ogies Group. then a fledgling information and telecom- munication product and solution provider. Since then, the optical fiber maker based in Wuhan. central China＇s Hubei Province, has grown into an ＂optical communications expert.＂

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。

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。

基于人工智能的多模态雷达自适应抗干扰优化算法

多模态雷达系统容易受到外界环境干扰,如天气条件、电磁干扰等,而这些干扰可能会影响多模态雷达数据的准确性和稳定性。多模态雷达的抗干扰性能决定雷达的测量精度,因此,为提升多模态雷达的抗干扰能力,提出基于人工智能的多模态雷达自适应抗干扰优化算法。该算法以多模态雷达信号模型为基础,分析距离速度同步欺骗干扰、频谱弥散干扰原理,计算欺骗干扰时雷达接收的总回波信号。将计算的回波信号结果输入至人工智能的YOLOv5s深度学习模型中,通过模型的训练和映射处理,完成多模态雷达自适应抗干扰优化,实现雷达欺骗性信号干扰抑制。测试结果显示,该算法的干扰对消比结果在0.935以上,干扰输出功率结果在0.017以下,能够可靠完成多干扰和单一干扰两种干扰抑制,实现多模态雷达自适应抗干扰优化。

非平稳强噪声环境中的音频信号端点检测系统

为提高音频信号端点识别能力,设计一种非平稳强噪声环境中的音频信号端点检测系统。构建音频信号端点检测硬件单元,利用预处理单元对音频信号进行预加重、分帧以及加窗处理后,端点检测单元在提取处理音频信号的MFCC倒谱距离特征、频带方差特征的基础上,依据动态阈值估计策略确定恰当阈值;通过双特征参数双门限法来实现对音频信号起止点的确定以及语音帧和非语音帧的分离;利用包络确定延时单元,防止噪声段被错误识别为语音段,避免出现拖尾太长问题。实验结果表明,所设计系统可实现非平稳强噪声环境音频信号端点检测,检测误差满足设定要求。

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。

典型后门耦合目标回波信号特性分析

构建了典型后门耦合目标,从时域和频域两个维度对目标进行了回波特性仿真,发现目标的孔缝-腔体结构出现强耦合时回波频域波形可观察到幅度凹坑,且强耦合频率时的回波时域波形呈双峰状,与非强耦合回波存在明显差异。通过改变后门耦合目标尺寸和形态仿真验证了所发现的回波信号特征规律,利用发现的回波信号特征规律可从回波信号中提取出未知目标腔体后门强耦合微波参数。

基于变分信号分解的脉冲多普勒雷达抗扫频式干扰方法

针对脉冲多普勒(Pulse Doppler,PD)雷达遭受扫频式干扰时,接收机被干扰信号饱和导致的雷达虚警或漏警问题,分析扫频式干扰作用下PD雷达中频信号特征,提出基于变分信号分解的PD雷达抗扫频式干扰方法。利用目标回波时域稀疏性及干扰信号的频域窄带特性,通过极大极小惩罚项和2阶变分惩罚项分别约束中频信号中的目标回波脉冲串分量和干扰分量,设计了基于交替方向乘子法的迭代算法求解优化问题各分量。保留目标回波脉冲串分量,滤除扫频中频分量,从而抑制干扰对雷达的影响,并通过仿真和实测数据验证方法的有效性。研究结果表明:所提抗干扰方法在信干比-20 dB扫频式干扰作用下能够有效抑制扫频式干扰对PD雷达的影响,显著提高PD雷达的抗干扰性能。

基于频率细化的和差对消主瓣抗干扰研究

目前,大多数雷达抗干扰都是围绕抗旁瓣干扰开展工作,且取得了一定的效果。当面对主瓣干扰,尤其是主瓣压制干扰时,由于干信比过高,回波信号完全被淹没在干扰信号中,且常规的旁瓣抗干扰策略无法起效,导致雷达无法在主瓣干扰方向检测出真实目标。抗主瓣干扰需求迫切,技术难度大,将体现未来雷达的核心竞争力。对此,文章通过分析多种主瓣抗干扰在工程实现上的可行性,提出基于和差通道对消的方法,利用和波束和差波束这两个通道来对输入干扰进行对消。通过优化处理算法,提高对消性能,实现主瓣抗干扰功能。

强噪环境下分频段数字音频信号精细化采集研究

在强噪环境下,为了获取高质量、低失真度的数字音频信号,提出一种强噪环境下分频段数字音频信号精细化采集方法。通过麦克风设备获取音频信号,利用LM4550芯片对其作采样、编码等处理后生成数字音频信号,基于AC-97单元接收数字音频信号,利用频段分割器对其作频带分解,获得互不重叠子频段数字音频信号。采用多窗谱谱减法对其去噪,利用数据通信接口将其传输给LM4550芯片,在完成模拟信号转换后,通过耳机输出,实现数字音频信号精细化采集。实验结果表明,该方法处理后的各子频段数字音频信号有用信息得以完整保留,并提高了信号波形的规整度和规律性,强噪声环境下数字音频信号的PESQ指标达到4.08以上,最大失真度为3.74%。