一种区分MFSK与MSK信号的新方法

研究了利用循环平稳统计量处理数字信号调制识别问题,识别对象包括MFSK(多进制频移键控)以及MSK(最小频移键控)信号.首先对调制信号复包络的一阶矩进行了提取,然后根据该特征提出了一种新的区分MFSK与MSK信号的调制识别方法并与经典的DMRA算法[1]进行了比较,最后利用人工神经网络实现了识别性能的计算机仿真.     

一种简单多径信道下的调制识别方法

为解决简单多径条件下调制识别类型少、难以工作于低信噪比下的问题,提出了一种基于联合特征参数的调制识别方法。根据简单多径下不考虑多普勒效应影响这一条件,利用调制信号的延迟相关和瞬时自相关特性,并结合高阶累积量特征对幅移键控(ASK)、相移键控(PSK)、频移键控(FSK)共8种信号进行分类识别。仿真结果表明,在信噪比大于4 dB时,简单多径条件下的各类调制信号正确识别率接近100%。     

基于峰度和小波变换的超短波信号调制识别

针对FM,MSK,QPSK三种具体调制方式,由于在高斯白噪声环境中小波变换幅度方差区分MSK,QPSK调制信号效果较差,以及在不同信噪比条件下零中心归一化瞬时幅度谱密度的最大值对FM,MSK和QPSK识别效果的下降,提出利用峰度和基于小波变换特征量的方法对信号分类识别。该方法首先利用峰度进行模拟与数字调制信号的类间识别,然后采用基于小波变换系数提取的特征量对两种数字调制信号进行识别分类。采用决策树分类方法,利用Matlab对该方法进行仿真验证,仿真结果表明该方法具有较好的识别效果。     

改进的MSK在曼彻斯特码数据传输中的应用

本文介绍了MSK(最小频移键控)调制解调的基本原理及设计方法，并对用Costas环提取载波的解调方案进行了改进，解决了载波提取和定时提取相互干扰的问题。最后通过仿真将它与常用的4PSK(四相绝对相移健控)的抗噪声及频谱性能进行了比较，得出MSK调制可用于测井技术来提高传输速率的重要结论。     

基于小波变换的MSK信号码速率盲估计

针对最小频移键控调制信号的码速率估计问题,提出一种基于Haar小波变换的MSK信号码速率盲估计方法。首先对接收信号作傅里叶变换得到信号频谱,对频谱频点分析粗估计信号的码速率,接着通过粗估计的码速率选取短时傅里叶变换窗函数长度和3个小波尺度,利用短时傅里叶变换得到信号瞬时频率变化,再利用小波的边缘检测特性对信号瞬时频率序列相位跳变点检测,最后对检测结果作频谱分析,估计频率得到MSK信号的码速率。仿真结果表明,高于信噪比门限时本算法可以对MSK信号码速率有效估计。     

基于压缩采样的PSK信号自动调制识别方法

N次方非线性变换方法是通信信号自动调制识别的常用方法,该方法对于相位键控(PSK)信号较为有效。但是,该方法要求的采样率通常要远高于Nyquist速率,这无疑给模拟数字转换器(ADC)带来了巨大的压力。本文利用相位键控(PSK)信号经过非线性变换后频谱的稀疏特性,提出了一种利用压缩采样数据实现PSK信号自动调制识别的方法。文中引入了压缩感知理论,并给出了利用压缩采样数据重构PSK信号非线性变换后频谱的方法,该重构频谱可用于自动调制识别及载频和符号率估计。     

一种基于相位信息的MSK软件解调方法

首先介绍了数字调制信号(包括PSK，FSK，QPSK，OQPSK和MSK等)的演化背景，然后重点介绍了MSK的调制解调原理，提出了一种基于瞬时相位信息的MSK解调方法，并进行了仿真实验，实验结果证明了该方法的有效性。     

Link16数据链中的MSK技术

Link16是目前发达国家使用的较为先进的数据链,它在调制方式、信源/信道编码、加/解密等方面都采用了先进的技术.介绍了Link16在调制方式上采用的最小频移键控(MSK)技术,并分析了MSK信号的性能.通过与FSK,2PSK信号的对比突显MSK信号的优点.正因为Link16采用了MSK技术,在带宽利用率以及系统容量方面都优于其他几种数据链.     

基于瞬时相位差分的MPSK信号识别与参数估计

在现有MPSK信号调制样式识别方法基础上,提出对QPSK、OQPSK、π／4QPSK和8PSK这四种星座图及频谱特征具有一定相似性的MPSK信号进行分类识别及参数估计的方法。识别和参数估计方法建立在瞬时相位差分统计特性和频谱分析基础上。对实际采集的信号进行实验的结果表明,该方法在信噪大于5dB时具有较高的调制样式识别和码速率估计精度。     

基于时频分析和RBF神经网络的调制识别

提出了利用Wigner-Ville分布区分FSK、PSK、FM和BSS信号的自动调制样式识别方法，利用Wigner-Ville分布提取调制信号的瞬时频率特征，用径向基(RBF)神经网络根据提取的特征参数识别这四种信号，计算机仿真结果证实了该方法的有效性和正确性。     

Study on hybrid pattern recognition algorithm for modulated signals

A combined feature extraction and recognition method is proposed based on higher-order spectrum, cyclic spectrum and time-frequency characteristics. In the application of this method, α-dimensional features, quadratic spectral characteristics and Fourier transform spectral characteristics of the signal are used to extract three characteristic values including the envelope means (EM) of α plane, the recursive normalized frequency component detection value (RNFCDV) and the quadratic spectrum normalized frequency component detection value (QSNFCDV), which have the merits of less identification parameters, insensitive to noise, less computation, high recognition rate, and multi-species identification. With this method, simulation results show that the recognition rate is more the 98% with the signal to noise rate (SNR) not less than 6 dB. And the performance of this method is better than the common recognition algorithms. There are eight types of signal, such as amplitude modulation (AM), phase modulation (PM), amplitude shift keying (ASK), frequency shift keying (FSK), phase shift keying (PSK), minimum shift keying (MSK), quadrature amplitude modulation (QAM) and direct sequence spread spectrum (DSSS), have been used to validate the feasibility of the method.     

Efficient Pulse Shaping Using MSK or PSK Modulation

The increasing requirement for high data rate, bandwidth efficient digital radio systems has led to the development of MSK-type modulation methods designed to achieve a compact signal spectrum. These modulation methods include sinusoidal frequency shift keying (SFSK), special MSK-type pulse shapes, and multiamplitude minimum shift keying (MAMSK). When more compact signal spectra are required, bandlimited filtering must be introduced. This note considers the use of conventional MSK or PSK modulators followed by newly developed bandlimited pulse shaping filters. With this approach, it is shown that MSK and offset QPSK modulators yield identical signals on the channel when filtered by properly designed bandlimited pulse shaping networks.     

小波包转换域PSK信号的模式识别

提出并采用信号的连续小波包分解的方法对BPSK、QPSK、8PSK数字调制信号进行模式识别。首先,根据3种调制信号的特点设置目标信号模板,然后将其分解到小波包子域形成子域模板并预先存储。执行识别任务时,将实际信号进行小波包分解,并在各小波包子域和子域模板作匹配相关,根据相关运算的结果完成识别。由于小波包分解的频带划分比小波分解的频带划分精细,所以识别的正确率更高。文中采用Monte Carlo法产生信号,采用Matlab进行仿真。仿真结果表明,采用小波包分解的识别正确率更高,尤其是在低信噪比环境下,该方法也能实现调制信号的精确识别。     

Multifrequency minimum shift keying

A new modulation scheme that produces a constant envelope continuous phase signal set with a compact power spectrum and power efficiency better than that of MSK is proposed. The scheme can be implemented by quadrature-carrier multiplexing of two frequency/phase modulated signals of the type NFSK/2PSK, both with the same frequency in each transmission interval, and with sinusoidal symbol shapes. The generated signal can be viewed in each transmission interval as an MSK signal at one of the N frequencies and is referred to as multifrequency minimum shift keying (MF MSK). Modulation, demodulation, and synchronization circuits are described, and the spectral properties and power efficiency on the AWGN channel are analyzed. Combining a number of attractive attributes such as constant envelope, excellent spectral properties, high power efficiency, and self-synchronization capability, the proposed modulation format lends itself to a variety of applications, one of them being the digital satellite link     

雷达信号有意调制的粗分类和细分类识别方法

针对雷达信号脉内有意调制中2类典型调制信号,即相位编码(PSK)信号和调频(FM)信号,提出了一种由粗到细的方法进行脉内识别。首先,对接收到的雷达信号利用其3 dB带宽明显不同的特点,进行类间粗分类,识别出PSK信号和FM信号;然后,针对PSK信号和FM信号类内特征的不同,提出了利用信号的小波脊频特征,来对雷达信号进行类内细分类识别的方法,使PSK信号被细分类为BPSK信号和QPSK信号、FM信号被细分类为LFM信号和NLFM信号,从而完成了典型雷达信号的有意调制的识别。仿真结果表明,在一定信噪比下,此识别方法真实有效。     

一种基于FPGA的MSK调制器设计与实现

首先分析了MSK调制信号的特点以及功率谱,然后根据软件无线电的思想,用可编程器件FPGA实现了基带信号的MSK调制,主要包括串并转换、数字频率合成、基带调制与中频调制等部分.     

A New Two-Branch Amplification Architecture and its Application with Various Modulated Signals

This paper proposes a new two-branch amplification architecture that combines baseband signal decomposition with RF front-end optimization. In the proposed architecture, the filtered modulated signals are separated into two components that are then amplified independently and combined to regenerate an amplified version of the original signal. A branch with an efficient amplifier transmits a low-varying envelope signal that contains the main part of the information. Another branch amplifies the residual portion of the signal. The baseband decomposition and parameters of the RF part are optimized to find the configuration that gives the best power efficiency and linearity. For M-ary quadrature amplitude modulation （M-QAM） signals, this technique is limited in terms of power efficiency. However, for filtered continuous phase modulation （CPM） signals, especially for minimum shift keying （MSK） and Gaussian MSK （GMSK） signals, high power efficiency can be achieved with no significant impact on the overall linearity. The results show that this technique gives better performance than the single-ended ctass-B amplifier.     

JTIDS的误码率性能分析

介绍了联合战术信息分配系统(JTIDS)战术数据链的信号流程,分析了JTIDS中循环码移位键控(CCSK)扩频、RS纠错编译码和最小频移键控(MSK)调制解调技术,研究了CCSK和RS编码在高斯白噪声环境下的抗干扰性能,建立了JTIDS性能分析模型,并使用MATLAB进行了仿真,仿真结果验证了采用CCSK扩频和RS编码...     

基于瞬时幅度特征的连续相位调制信号识别

针对非合作通信系统中连续相位调制（CPM）信号识别难的问题,提出一种CPM信号识别新方法。算法以信号的瞬时幅度谱为特征,结合谱线检测,实现了CPM信号与幅移键控（ASK）、正交幅度调制（QAM）、相移键控（PSK）、频移键控（FsK）信号的区分。算法无需各种参数估计及同步等预处理过程,仿真实验结果表明,在信噪比不小于4dB时,CPM信号正确识别率达到95％以上。与已有算法相比,本文所提算法具有计算量小、实现简单和低信噪比下识别率高等优点。