雷达信号包络特征的检测与分析

雷达信号的分类识别是电子对抗的一个重要方面 ,而雷达信号包络分析是识别它的一种重要方法 ,它利用检测设备截获敌方雷达信号 ,通过分析它的包络特征来识别雷达信号以便于干扰或反干扰。采用平滑、微分的方法对包络进行处理 ,获得它的各项参数信息 ,从而达到对雷达信号识别的目的     

短波环境下跳频信号检测

短波电磁环境复杂,定频信号、扫频信号、突发信号等大量干扰信号存在,使得跳频信号的检测存在困难,首先利用短时傅里叶变换将信号变换到二维时频平面上,用功率谱对消的方法来清除大部分定频、扫频等信号;其次根据跳频信号不同于定频信号的特性,提出了一种单元平均选小的恒虚警概率准则(CASO-CFAR),将其扩展到二维并应用到时频平面;最后利用形态学图像处理方法中的开和闭运算及中值滤波器对判决后的二值图像进行处理,进一步解决了判决后残留的星点噪声和信号空洞问题。实验表明,该方法能够抑制定频干扰,凸现跳频信号,为跳频信号的分选、解调等后续工作提供了良好的基础。     

On the notion of control signals in digital designs

The concept of control signals is fundamental to digital design. It evokes the notion of one or more signals that influence computation on other signals in a system, and regulate the behavior of the system. A formal definition of control signals is presented. It is argued that knowledge of the control signals in a complex design such as a microprocessor or a computer is crucial to the comprehension and specification of the design and that knowledge of the control signals of a design leads to a more efficient hardware implementation. The identification of control signals in two microprocessors are presented as examples     

突发自适应调制信号的调制识别算法研究

针对突发自适应调制信号中的PSK和QAM调制方式识别问题,本文提出了一种能够识别BPSK、QPSK、8PSK以及16QAM、32QAM、64QAM、128QAM、256QAM八种信号类型的盲识别算法。该算法首先对信号的循环平稳性进行了分析和讨论,给出了利用循环高阶累积量的特征实现信号识别分类的理论依据。然后,提出了三种基于循环累积量的特征分别实现了QAM和PSK类间识别、MPSK类内识别以及方形QAM与十字形QAM的识别。最后通过对MQAM信号的瞬时幅度分布特性的深入研究和分析,提出了一种基于瞬时包络平方的方差的特征实现了QAM的类内识别。该算法选择了二叉树支持向量机作为识别分类器,并设计了一种新的识别流程完成了对上述信号调制方式的识别。该算法无需精确同步,对载波相位具有较好的鲁棒性,并能够对中频信号进行识别。仿真实验表明,该算法能够实现在较低信噪比条件下突发信号的识别。      

多相码雷达信号识别与参数估计

该文研究了多相码雷达信号的识别与参数估计。首先估计接收信号的码元宽度,利用多相码信号的时宽和码元宽度已知的条件下可以确定相位调制规律的特点,构造本地参考信号;把该参考信号与接收信号共轭相乘,当本地参考信号与接收信号的调制方式一致时共轭相乘的结果是正弦波,利用这个性质进行调制方式识别;估计该正弦波的频率作为载频估计;最后分析了存在同步误差时的频谱结构。仿真结果显示本算法可以在低信噪比条件下对多相码信号进行识别,并得到载频和码元宽度的精确估计值。     

Cyclic spectral analysis of continuous-phase modulated signals

Continuous-phase modulated (CPM) signals play a prominent role in modern communication systems due to their desirable constant-modulus property and the ability to control their power and bandwidth efficiencies. Popular CPM signals include the classical minimum-shift keyed (MSK) signal, the LREC family of signals also known as continuous-phase frequency-shift-keyed (CPFSK) signals, and Gaussian MSK, which is used in state-of-the-art GSM and PCS mobile communication systems. CPM signals, like virtually all man-made communication signals, are known to exhibit cyclostationarity, which implies that their probabilistic parameters, such as mean, second moment, and higher order cumulants, are almost-periodic functions of time. A novel representation of CPM signals as a sum of PAM signals is presented for both integer and noninteger modulation index cases. Then, the Nth-order cyclostationarity properties of binary CPM signals are derived in terms of Nth-order temporal and spectral moment and cumulant functions. Moreover, the case of M-ary CPM signals is briefly addressed. The results are illustrated with simulations involving MSK, LREC, and GMSK signals     

基于循环自相关的OFDM调制识别方法

针对通信信号的调制识别问题,首先根据通信信号的循环平稳性,提出一种基于循环自相关的OFDM信号和单载波信号的调制识别算法,然后将小波多分辨分析理论与调制信号的瞬时特征以及高阶累积量相结合,提出一种基于小波分解的单载波信号识别方法,在此基础上采用分层结构的神经网络分类器对OFDM,2ASK,4ASK,2PSK,4PSK,8PSK,16QAM这7种调制信号进行识别。仿真结果表明该方法具有良好的分类性能,且对噪声不敏感。     

Improving the quality of the audio sources using Gaussianity reduction technique

This research has developed a novel technique that is based on the fundamental property of background and foreground signals. Background signals are a result of the inferential summation of large number of sources, while the foreground signals are a result of limited number of sources. This makes the statistical properties of the signal very different. Using negative entropy, this article demonstrates that it is possible to obtain the foreground signals from the mixture of foreground and background signals. The technique is based on mixing the noisy recording with a similar known signal and separating the signals using negative entropy based independent component analysis (ICA). The results indicate that the technique is successful in significantly improving the quality of the audio signals.     

基于小波分解的OFDM与单载波信号识别

针对多径信道下OFDM信号的识别问题,提出了一种基于小波分解获得细节特征的信号识别方法.由于不同调制方式信号的细节分量在同一分解水平下存在较大差异,而细节分量几乎包含了信号的全部细节信息,从而直接反应信号的变化情况.通过理论推导和仿真测试证明单载波和OFDM信号在进行多层小波分解后,每层对应细节分量的幅度值具有不同的变化,然后利用其幅度差作为特征参数,并基于最近邻法判决规则实现单载波信号和OFDM信号的有效识别.仿真结果证实了该方法在较低信噪比下识别的正确性和可行性.     

Optical phase conjugation of multiwavelength signals in adispersion-shifted fiber

Optical phase conjugation (OPC) of multiwavelength signals in a dispersion-shifted fiber (DSF), which can be used for dispersion compensation in the wavelength division multiplexing communication system, is theoretically studied. The multiwavelength phase-conjugate signals are generated by four-wave mixing (FWM) in the dispersion-shifted fiber. There are the pulse-shape distortion and the induced frequency chirping in the phase-conjugate signals owing to pump depletion and the cross-phase modulation among the signals and phase-conjugate signals, respectively. The FWM among the pump wave, signals, and phase-conjugate signals causes unequal conversion efficiencies for the multiwavelength signals and enhances the induced frequency chirping in the phase-conjugate signals. The induced frequency chirping may deteriorate the restoration of the pulse shape. Both the pulse-shape distortion and induced frequency chirping increase with the signal and pump powers. The formula for the induced frequency chirping that is only caused by the signals through cross-phase modulation is derived. The requirement of the signal power in the dispersion-shifted fiber for the restoration of the pulse shape by the optical phase conjugation is estimated and numerically verified     

中频采样的线性调频脉冲信号恢复高频信号的研究

提出了一种将中频采样信号恢复为高频信号的算法,证明了线性调频脉冲信号的频谱特性与信号中频无关,给出了方法可行的限制条件。     

数字卫星电视接收天线仰角方位角极化角调试探讨

数字电视正以迅猛之势发展,目前数字电视信号主要是通过卫星传输,数字卫星电视信号的接收方法与模拟卫星电视信号的接收方法相同,利用室外抛物面状天线将数字卫星电视信号——电磁波接收下来,但由于数字电视信号的特点,接收数字电视卫星信号时的“寻星”过程远比接收模拟卫星电视信号困难得多,为此对数字卫星电视接收天线仰角、方位角、极化角的调试进行探讨。     

Reconstruction of aperiodic FRI signals and estimation of the rate of innovation based on the state space method

In the absence of observation noise, it is known that it is possible to develop exact sampling schemes for a large class of parametric non-bandlimited signals, namely, certain signals of finite rate of innovation (FRI signals), either periodic or aperiodic, such as streams of Diracs, nonuniform splines or piecewise polynomials. A common feature of such signals is that they have a finite number of degrees of freedom per unit of time and they can be reconstructed from a finite number of uniform samples of the filtered signal. Unfortunately, the accuracy of such reconstruction substantially degrades when the samples are distorted by noise. For the case of periodic FRI signals, good algorithms based on the state space method have been proposed which are robust against noise. However, in the case of aperiodic signals, these algorithms may still fail to accurately reconstruct the signals due to ill-conditioning problems that often arise in the matrices involved. This paper proposes a new reconstruction method for aperiodic FRI signals that is also based on the state space method but has a considerably better numerical conditioning than previous reconstruction algorithms. This advantage is achieved by using a frequency domain formulation.     

基于时频分析的多跳频信号盲检测

为了减小低信噪比下干扰和噪声对跳频信号检测的影响,提出一种基于时频分析的多跳频信号盲检测算法。针对跳频信号、定频信号、高斯白噪声具有的不同时频分布特点,该算法利用短时傅里叶变换得到的时频图构造时频对消比;理论分析得到各信号的时频对消比是不同的,因此将其作为检测统计量,实现高斯白噪声背景下跳频、定频信号的盲检测。仿真结果表明,本文算法具有抗噪声功率不确定性能;与改进型功率谱对消法相比,本文算法在低信噪比环境下,具有更高的跳频信号和定频信号检测概率。此方法也能实现存在定频信号、扫频信号和突发信号干扰的复杂电磁环境中跳频信号盲检测,当信干比为5 dB且跳频信号的检测概率达到100%时,本文算法比改进型功率谱对消法改善信噪比10 dB;在干噪比为0.05 dB时的虚警概率几乎为0。      

混合激光制导信号分选与解码研究北大核心CSCD

根据激光告警实际需求,开展混合激光制导信号的分选与解码研究。分析了混合激光制导信号特征,提出了混合激光制导信号分选和解码方法,编写了混合激光制导信号分选与解码软件。对PRF与PRF、PRF与PIM、PIM与PIM等三类混合信号进行了分选和解码。结果显示,利用骨架周期分析方法,能够正确分选包含PIM信号的混合信号,且分选与解码总用时较短,能够满足实际需求。     

高动态GPS中频信号仿真及验证

在研究在高动态条件下GPS软件接收机信号处理算法时,需要对高动态GPS数字中频信号进行仿真。本文在分析GPS数字中频信号数学模型的基础上,针对高动态载体接收的GPS信号深入研究,提出了一种高动态信号仿真方法,详细阐述了信号仿真的步骤,在MATLAB上实现了对GPS数字中频信号的仿真,最后在GPS软件接收机上验证了中频仿真信号。检验结果表明,本文提出的仿真方法可以为研究高动态GPS软件接收机算法提供可靠的信号源。     

用小波变换的模极大值提取调制信号频率

利用小波变换系数的模值与信号奇异性指数之间的关系,从调频信号中提取出调制信号的频率.其方法是:对调频信号进行小波变换,取适当尺度上的小波系数进行平方,得到小波变换模极大值的分布曲线,对该曲线进行小波强制滤波,得到反映调制信号频率的光滑曲线,计算该曲线的频率,即可得调制信号的频率.经过计算机仿真,证明该方法是可行的.     

小波变换在摆式列车控制信号分析中的应用

列车横向加速度具有较低频率特性，是受到列车运行速度影响而变化的非平稳信号。根据小波的多分辨率分析原理，应用Ｄａｕｂｅｃｈｉｅｓ正交小波对列车进入弯道横向加速度信号进行多分辨率分析，消去列车横向振动信号，提取出列车通过弯道时的剩余离心加速度信号，以便及时推确地为摆式列车提供倾摆控制指令。     

基于排序时频特性的雷达脉内调制信号识别

提出了一种基于排序时频特性的雷达脉内调制信号识别算法.该算法可分为三步:首先,通过检验信号时频曲线的互易回归特性,识别出线性调频信号;然后,通过检验信号时频RANKIT图的正态性,识别出常规信号;最后,检验信号平方后时频RANKIT图的正态性,用以区分二相编码与四相编码信号.仿真结果表明,该算法无需接收信号的任何先验知识,在较低信噪比条件下可实现对常用雷达脉内调制方式的有效识别.     

基于小波变换的通信信号识别算法

通信技术的数字化已经是现代通信发展的趋势.为识别出通信信号中的数字信号的调制方式,分析了解析信号以及归一化处理后的数字信号经过小波变换后的特点,提出直接提取信号小波变换后的频域特征的算法.该算法无需设置判决门限,可以更简单、直接地实现数字信号与其它信号的类间区分以及数字信号之间的区分.通过仿真表明,该方法可有效区分PSK、FSK、QAM与AM、FM、SSB、CW、噪声.