一种虚拟信号分析仪的设计

介绍了虚拟信号分析仪的结构和现代信号的处理方法。基于傅立叶变换、短时傅立叶变换和小波变换,提出了一种虚拟信号分析仪的系统软件模块的实现方法。该方法利用这三种变换,对信号进行多次处理,能够得到信号的时域、频域和时频域信息,能够对信号进行降噪处理。实验表明,利用此分析仪,能够测量信号的周期、频率、瞬时频率、时频变换趋势和奇异点,并且能以图形的形式显示出来。     

强噪声环境下声波信号时延估计方法的比较

声波信号时延的准确估计是实现强噪声环境下声学法高精度测温的关键。介绍了声学测温中基于互相关函数、人工神经网络和小波变换等几种典型的信号时延估计方法．对这3种时延估计方法的实现原理分别进行了论述，分析比较了它们的优缺点，相比于其他两种方法，小波变换技术更适合于强噪声环境下的声波信号的时延估计。     

基于小波的周期信号中瞬态冲击特征提取

小波变换具有优良的时频分析特性,利用小波变换提取周期信号中的微弱瞬态冲击非常有效。为了消除ＭＡＬＬＡＴ算法中的频率混淆,本文提出了一种改进的二进离散小波变换快速算法,并成功地利用小波变换提取了某型涡喷发动机滚珠轴承的早期故障特征,实现了傅立叶变换所达不到的效果。     

基于分数阶Fourier变换的微弱LFM信号检测

为了提高侦察系统对微弱LFM信号的检测能力,文章提出了一种基于分数阶Fourier变换的微弱LFM的检测方法。首先,分析LFM信号在离散分数阶Fourier变换计算条件下的输出信噪比,得出当观测信号的采样点数增大时,分数阶Fourier变换可有效改善输出信噪比。利用该结论,提出了通过提高信号的采样频率或者对已采样信号作插值的方法,改善分数阶Fourier变换对微弱LFM信号的检测。最后,仿真验证该方法是有效的。     

调频连续波SAR改进的频率尺度变换算法(英文)

本文提出了一种调频连续波SAR改进的频率尺度变换算法。调频连续波SAR在运动过程中持续不断地发射和接收信号,这种运动导致了回波信号的伸缩,对波前重建产生了严重的影响。推导了回波信号模型,给出了信号的距离-多普勒域表达式,分析了由于天线不断运动而导致的相位变化与方位向频率之间的关系。改进的频率尺度变换算法补偿了这种相位变化,实现了目标的精确成像,仿真结果表明了分析的正确性和算法的有效性。     

基于周期FRFT的多分量LFMCW雷达信号分离

 多分量线性调频连续波(LFMCW)信号的截获和特征提取是雷达情报侦察的难点,为了实现对多分量LFMCW信号的快速检测和有效分离,提出了一种基于周期分数阶Fourier变换(PFRFT)的多分量LFMCW雷达信号分离新方法。首先介绍了PFRFT,分析了PFRFT和FRFT之间的关系,讨论了LFMCW信号的PFRFT特征。然后给出了一种离散PFRFT的计算方法,结合周期分数阶Fourier域(PFRFD)的窄带滤波和CLEAN算法实现了多分量LFMCW信号的分离。仿真结果表明:①PFRFT的计算效率较周期Wigner-Hough变换(PWHT)具有明显优势;②LFMCW信号分量在特定PFRFD中具有能量峰值,分离后能较好保留时频特征;③当两个LFMCW信号分量的功率相差较大时,适合在PFRFD分离,反之适合在时域分离;④当信噪比(SNR)为0 dB时,两个具有相同功率的LFMCW信号分量分离后,与初始信号分量的相关系数都达到了0.9以上。     

重量的一种遥测式监测系统

本文提出一种重量信号的无线传输和测量方法。重量信号经传感顺转换成电信号，再经Ｖ／Ｆ变换后调频发射，接收信号解调后单片机处理。单片机的信号处理采用电子计数器测频方法，经过计算送显示单元，实现重量信号的遥测。     

小波域的自适应波束形成算法

在分析传统自适应波束形成的基础上,首次提出了一种小波域的自适应波束形成算法。与通常的自适应波束形成算法相比,该算法利用小波变换对小波空间进行了分解,信号经小波变换自相关性会下降,收敛速度提高,同时在此分解过程中,根据信号与白噪声在不同尺度上的小波变换模极大值表现完全不同的特性进行信号的消噪。理论分析和仿真结果表明了该算法收敛速度较快,且计算量增加较少,易于实时实现,而且具有较好性能。同时仿真实验表明该算法收敛速度与小波基和尺度的选择有关,尺度越大收敛速度越快;对于同一小波基系列,小波基的正则性越好收敛速度越快。     

基于小波变换的非平稳信号趋势项剔除方法

分析了空间飞行器遥测信号处理传统趋势项剔除方法的优势和不足,提出了基于小波变换的非平稳信号趋势项剔除方法。这种方法通过滤波器组将信号分解与重构,实现趋向性信号与零均值平稳随机信号的分离。仿真实验表明,该方法简单、高效,适用于非平稳随机信号的处理,是一种实用的趋势项剔除方法。     

非合作无源探测中的参考信号提纯新方法

非合作无源探测系统通过直达波提纯来获取参考信号,参考信号的纯净程度对系统探测性能具有重要影响.针对非合作无源探测中的参考信号提纯问题,提出了一种基于稀疏特性的参考信号提纯新方法.首先将参考通道接收的混合信号变换到对时延敏感的分数阶傅里叶变换域上,并对直达波信号和多径干扰信号在分数阶傅里叶变换域上的稀疏特性进行了分析;然...     

Signal Detection Using Bit-Slice Microprocessors

A bit-slice microprocessor configuration is presented which is applicable to implementation of real-time signal detection algorithms. The general hardware configuration and appropriate software functions are described. General algorithms which are of wide utility in signal detection applications are discussed in the context of the defined hardware configuration. To facilitate the presentation and indicate the practicality of this system configuration, the application of the hardware configuration and software techniques to target detection for passively received signals using multiple receive beams is discussed.     

基于软件无线电的机会信号实时盲分离系统

在复杂的电磁环境中,往往存在多种频率交叠的机会信号,为利用机会信号进行定位增加了难度。针对这个问题,提出了一种基于软件无线电的机会信号实时盲分离系统。系统的硬件部分是在FPGA中实现等变自适应盲分离算法的,实现了AD采集后的复数域混合信号的分离。分离后的信号通过USB3.0数据线上传到上位机中进行存储、识别和实时显示。算法的FPGA实现采用流水线架构和浮点运算设计来提高信号的实时处理能力和数据计算精度。实测结果表明,该系统能够实时分离多路复数域混合机会信号。     

A Recursive Method for Signal Resolution

A recursive method is given for resolving signals overlapping in time. Assume that the signal waveform is known and several signals are received. The signals (of unknown number) may overlap with one another and the amount of time delay of each individual signal is unknown. The signals are corrupted with additive white Gaussian noise. The problem is to estimate the number, the amplitudes, and the time delays of the overlapping signals. Assume that at a certain instant tk-1 estimates have been made on the number of signals arriving in the time interval (O, tk-1) and the amplitudes and time delays of these signals. Using these estimates, we test at tk the hypothesis H1 that a new signal arrives at tk against the null hypothesis Ho that no new signal arrives. The decision gives the number of signals arriving in the time interval (0, tk); the parameters are then re-estimated. The overlapping signals are detected and resolved, and the estimates are improved at each stage. The system is analyzed in detail, and computer-simulated results are presented.     

通信信号调制识别综述

随着频谱信息资源愈发紧张,信号的调制处理方式也愈发多样化.由于通信信号的调制识别广泛应用于民用和军用领域,所以,对调制方式进行识别的研究具有极其重要的意义与战术价值.首先,根据大量文献,对基于最大似然函数和特征提取的经典调制识别方法进行了系统地梳理;其次,从常用数据集、深度神经网络结构和现有识别算法等方面,着重介绍了深...     

信号仿真系统离散信号发送功能研究

离散量信号是民用飞机地面模拟试验中不可缺少的信号之一。基于某型号飞机地面模拟试验的需求,提出了简单可靠的离散信号电路设计方案,利用CMOS管和光电耦合器作为输入输出隔离器件,将TTL电平转换成离散量信号。采用电路仿真软件Multisim进行仿真分析,并结合某型号铁鸟试验验证。仿真分析及试验结果表明,该电路满足某型号飞机地面模拟试验对离散量信号的要求。     

Costas编码信号的循环谱特征分析与参数估计

研究了准确反映Costas编码信号特点的关键参数集合。基于循环谱相关密度估计方法,分析了Costas编码的循环谱特征及其与辐射源侍号参数的对应关系,提出了一种没有先验知识条件下Costas编码截获信号特征提取方法。通过对典型的Costas编码信号参数提取归一化均方根误差的计算,验证了该算法的有效性。     

ARINC429总线信号测试平台的设计

本文基于对ARINC429总线信号的分析,提出了ARINC429总线信号测试平台的设计,该平台可以及时发现测模块的潜在故障,有利于提高ARINC429总线信号模块产品的质量水平。该测试平台可以实现对各类包含ARINC429总线功能的模块进行自动测试,减少了专用测试设备的研制,极大的缩减了测试设备的研制经费和维护成本。     

Linear FM Signal Formats for Beacon and Communication Systems

This paper examines the capabilities of the class of linear FM spread-spectrum signals within the context of potential communications systems usage in order to establish some performance criteria and bounds that permit comparison with other spread-spectrum formats. A systematic basis is provided for parameter selection for this class of signals by examining the interaction a mong the frequency-modulation indices, time-bandwidth product, and cross-talk criteria that determine the number of effective linear FM signals (or channels) that can be used within the constraints of a bounded time-frequency region. A general expression is derived relating N, the number of useful signals, R2, a cross-talk parameter, ToWo, the mean time-bandwidth product, and ?max and ?min, the maximum and minimum FM rates of the signal set. Canonic signal processor structures are described for ensembles of linear FM signals that have either constant duration or constant bandwidth. It is then shown that the signal modulation format can be modified in accordance with classical paired-echo theory to expand the utility of this class of signals in both synchronous and nonsynchronous operations to yield the equivalent of time-division and code multiplexing. Possible applications for this signal format are discussed.     

Hybrid discriminative/class-specific classifiers for narrowband signals

The class-specific (CS) method of signal classification operates by computing low-dimensional feature sets defined for each signal class of interest. By computing separate feature sets tailored to each class, i.e., CS features, the CS method avoids estimating probability distributions in a high-dimension feature space common to all classes. Building a CS classifier amounts to designing feature extraction modules for each class of interest. In this paper we present the design of three CS modules used to form a CS classifier for narrowband signals of finite duration. A general module for narrowband signals based on a narrowband tracker is described. The only assumptions this module makes regarding the time evolution of the signal spectrum are: (1) one or more narrowband lines are present, and (2) the lines wandered either not at all, e.g., CW signal, or with a purpose, e.g., swept FM signal. The other two modules are suited for specific classes of waveforms and assume some a priori knowledge of the signal is available from training data. For in situ training, the tracker-based module can be used to detect as yet unobserved waveforms and classify them into general categories, for example short CW, long CW, fast FM, slow FM, etc. Waveform-specific class-models can then be designed using these waveforms for training. Classification results are presented comparing the performance of a probabilistic conventional classifier with that of a CS classifier built from general modules and a CS classifier built from waveform-specific modules. Results are also presented for hybrid discriminative/generative versions of the classifiers to illustrate the performance gains attainable in using a hybrid over a generative classifier alone.