基于Zoom-FFT改进DFT的辐射源信号载频频偏估计

为了研究辐射源的细微特征分析,针对目前主流的几种离散傅里叶变换(DFT)频偏估计算法分析载频频偏精度不够高的问题,提出一种基于细化快速傅里叶变换(Zoo-鄄FFT)的改进DFT算法。该算法先对离散采样的信号采用Candan算法进行粗估计,再将频谱峰值周围的频段进行细化放大,然后利用2N点DFT算法对残余频率精细估计。该算法综合了上述两种算法的优点,能够在适当信噪比环境下达到很好的估计精度。文中以二次雷达信号为研究对象,仿真分析验证了算法的可行性与有效性。     

一种改进的高动态QPSK信号解调算法

正交相移键控(QPSK)调制解调方式广泛应用于深空通信、数字卫星通信等高速系统中,高动态QPSK信号具有较大的多普勒载波频偏,针对现有的解调算法对QPSK信号频偏估计范围小、精度较低等问题,提出了一种改进的高动态QPSK信号解调算法。该算法利用基于Zoom-FFT的Quinn频率估计算法对载波频偏进行估计,将频偏估计分为粗估计和精估计两个过程,对估计所得频偏进行补偿后利用Costas环完成载波同步。在MATLAB中对算法进行了仿真,仿真结果表明,该算法能够实现对高动态大频偏QPSK信号的有效捕获,与传统的解调方式相比,该算法对载波频偏的估计范围更大,且具有更高的频偏估计精度和更好的误码性能。     

基于改进DFT相位差的正弦波频率估计

针对基于离散傅里叶变换( DFT)相位差的正弦波频率估计方法对频偏敏感的问题,提出了一种改进DFT相位差频率估计方法。首先推导了DFT相位差法频率估计的均方误差,然后提出了基于Rife插值的改进DFT相位差频率估计方法,较好地解决了正弦波频率估计对频偏敏感的问题。仿真实验结果表明,改进方法在各种频偏下均能取得较高的估计精度,估计性能接近克拉美罗限( CRLB)。     

GMSK通信系统中频偏估计改进算法

针对具有固定帧长和固定帧同步序列信号,提出了一种利用序列自相关特性进行频偏估计的方法。针对有记忆调制信号,对频偏估计方法再次改进,进一步提升了频偏估计性能,并分析了频率偏移对本方案频偏估计性能的影响。仿真表明,在误码率为0.06性能点,利用本文提出的频偏估计算法有2 dB的性能提升,且在高信噪比时性能将进一步提升。     

一种基于频率校正的BPSK信号高精度载频估计算法

为了实现BPSK信号载频的高精度估计,提出一种基于频率校正的高精度BPSK信号载频估计算法。算法通过非线性变换将BPSK信号的载频估计问题转化为对点频信号的估计,再用DFT对点频信号进行粗估计,针对DFT估计频率分辨率差的问题,采用相位差校正法对DFT估计频率进行校正,从而实现BPSK信号载频的高精度估计。最后,通过性能分析和计算机仿真验证了算法的有效性,其结果表明:该算法在低信噪比情况下能获得较好的估计精度,在高信噪比情况下,估计精度大幅提高。     

一种1090ES相位编码信号的同步算法

载波同步是对1090MHz扩展电文(1090MHz Extended Squitter,1090ES)的相位编码信号进行相干解调的前提和基础,研究针对这种调制方式的基于数据辅助的载波频偏估计算法。构建了1090ES相位编码信号的频偏估计模型,提出了一种基于遗传算法的频偏估计算法,详述了该算法的特点及其实现步骤,并通过MATLAB仿真,分析比较了该算法与Kay算法、Fitz算法及M&M算法的频偏估计性能。该算法的频偏估计范围可以达到采样频率的50%,在信噪比高于3 dB时,频偏估计的均方误差接近于修正的克拉美罗界,并且可以同时兼顾频偏估计精度和频偏估计范围。     

一种改进的CPFSK信号频率估计方法

针对突发信号解调中多普勒频偏大的问题,提出了一种改进的连续相位移频键控信号(CPFSK)频率估计方法.首先接收信号平方运算使信号的调制指数加倍,再通过一次离散傅里叶变换(DFT),用搜索信号平方谱谱峰的方法实现突发信号频率估计.仿真实验表明,在低信噪比条件下,该算法的频率估计精度比经典的相位差频率估计算法提高了20%;该算法与广泛用于高动态突发信号的频率插值估计算法相比,同道干扰信道下信干比改善可达4 dB,DFT长度缩短约1/3.     

星载AIS信号的频偏估计

星载自动识别系统(AIS)中信号存在严重的多普勒频偏,影响信号的正确解调,而传统的基于快速傅里叶变换(FFT)的频偏估计算法其估计范围无法满足需要.为此,提出了一种改进的自相关-FFT频偏估计算法,通过构造辅助函数以确定信号频偏的正负号,在此基础上对基于FFT的频偏估计算法进行改进,从而扩大频偏估计范围,实现对大的多普勒频移的估计.仿真和实验结果均表明,改进算法的频偏估计范围扩大为原来的2倍,具有很高的估计精度,十分接近修正后的克拉美罗界,且算法简单、易于实现.     

MIMO-OFDM迭代时变频偏估计算法

MIMO-OFDM是一种高速的通信技术,满足了未来舰载雷达协同通信时隙小、数据量大的要求。但是舰船间的相对速度会导致通信频率的不断变化,而且MIMO-OFDM技术对频偏又十分敏感,因此必须对时变频偏进行估计。本文假设每一帧信号的频偏都是随机变量,提出了利用期望最大化（EM）和最大后验概率（MAP）译码算法相结合的时变频偏估计和信号检测算法。计算机仿真结果表明,该算法可以准确地估计时变频偏,而且系统的误码率性能和频偏估计精度可以随着迭代次数的增多而提高。     

基于频偏校正的高精度频率估计算法

提出了基于频偏校正的频率估计算法的两种改进思想．以分别用于减少计算量和提高频率估计精度。新方法通过分析信号下变频前后自相关函数的关系来减少计算量。而利用N-1点的自相关值取平均作为N／2点的自相关值来提高估计精度。     

An OFDM scheme with a half complexity

The paper deals with an OFDM (orthogonal frequency division multiplexing) system based on filter-bank architecture. The known implementation uses a DFT (discrete Fourier transform) processor and a polyphase network (PPN). Even if it is based on complex components, in the final step it operates the real part extraction of the incoming signal. This leads to redundant operations in the DFT processor and in the PPN. Specifically, for the transmission of N complex symbol sequences at a given rate ½F, an N-point DFT processor and an N-branch PPN, both working at the rate F, are required. This implementation can be improved with a complexity reduction by a factor of two. In fact, in the paper an architecture is presented based on an N-point DFT processor and N-branch PPN at the rate F, for the transmission of 2N (in place of N) complex symbol sequences at the rate ½F     

Fast splitting alpha-rooting method of image enhancement: tensor representation.

In the tensor representation, a two-dimensional (2-D) image is represented uniquely by a set of one-dimensional (1-D) signals, so-called splitting-signals, that carry the spectral information of the image at frequency-points of specific sets that cover the whole domain of frequencies. The image enhancement is thus reduced to processing splitting-signals and such process requires a modification of only a few spectral components of the image, for each signal. For instance, the alpha-rooting method of image enhancement can be fulfilled through processing separately a maximum of 3N/2 splitting-signals of an image (N x N), where N is a power of two. In this paper, we propose a fast implementation of the a-rooting method by using one splitting-signal of the tensor representation with respect to the discrete Fourier transform (DFT). The implementation is described in the frequency and spatial domains. As a result, the proposed algorithms for image enhancement use two 1-D N-point DFTs instead of two 2-D N x N-point DFTs in the traditional method of alpha-rooting.     

基于导频辅助的DFT时变频率捕获算法

以线性调频信号为信号模型,围绕时变频率捕获算法展开研究。重点研究了传统的时变频率捕获算法——延迟自相关算法,然后针对延迟自相关算法无法在低信噪比下实现线性调频信号参数估计的问题,提出一种基于导频辅助的离散傅里叶变换(DFT)时变频率捕获算法。仿真结果表明,提出的算法和延迟自相关算法均基于2次快速傅里叶变换(FFT)运算实现了线性调频信号的频偏和频偏变化率的捕获,该算法具有更低的信噪比门限。     

TST-MUSIC for joint DOA-delay estimation

A multiple signal classification (MUSIC)-based approach known as the time-space-time MUSIC (TST-MUSIC) is proposed to jointly estimate the directions of arrival (DOAs) and the propagation delays of a wireless multiray channel. The MUSIC algorithm for the DOA estimation is referred to as the spatial-MUSIC (S-MUSIC) algorithm. On the other hand, the temporal-MUSIC (T-MUSIC), which estimates the propagation delays, is introduced as well. Making use of the space-time characteristics of the multiray channel, the proposed algorithm-in a tree structure-combines the techniques of temporal filtering and of spatial beamforming with three one-dimensional (1-D) MUSIC algorithms, i.e., one S-MUSIC and two T-MUSIC algorithms. The incoming rays are thus grouped, isolated, and estimated. At the same time, the pairing of the estimated DOAs and delays is automatically determined. Furthermore, the proposed approach can resolve the incoming rays with very close DOAs or delays, and the number of antennas required by the TST-MUSIC algorithm can be made less than that of the incoming rays     

利用DFT和迭代校正的正弦信号频率估计算法

对电磁信号的频率估计广泛应用于通信、雷达、导航和电子对抗等领域。针对正弦信号的频率精确估计,本文提出了一种利用DFT和迭代校正的频率估计算法,并与现有三种基于DFT的频率估计算法进行了性能仿真对比,分析结果表明,新算法的频率估计性能明显优于其他三种算法,可以得到非常逼近CRLB的频率估计值,迭代校正5次时,频率估计的RMSE距离CRLB不到0.07dB,而且没有估计误差平层,算法估计精度高,对频率的取值范围不敏感,性能稳定,迭代校正的复杂度较低,具有很好的应用价值。      

FSF MUSIC for Joint DOA and Frequency Estimation and Its Performance Analysis

In this paper, we present a tree-structured frequency-space-frequency (FSF) multiple signal classification (MUSIC)-based algorithm for joint estimation of the directions of arrival (DOAs) and frequencies in wireless communication systems. The proposed approach is a novel twist of parameter estimation and filtering processes, in which two one-dimensional (1-D) frequency (F)- and one 1-D space (S)-MUSIC algorithms are employed-in a tree structure-to estimate the DOAs and frequencies, respectively. In between every other MUSIC algorithm, a temporal filtering process or a spatial beamforming process, implemented by a set of complementary projection matrices, is incorporated to partition the incoming rays to enhance the estimation accuracy, so that the incoming rays can be well resolved even with very close DOAs or frequencies, using the 1-D MUSIC algorithms. Also, with such a tree-structured estimation scheme, the estimated DOAs and frequencies are automatically paired without extra computational overhead. Furthermore, some statistical analyses of the undesired residue signals propagating between the 1-D MUSIC algorithms and the mean square errors of the parameter estimates are derived to provide further insights into the proposed approach. Simulations show that the new approach can provide comparable performance, but with reduced complexity compared with previous works, and that there is a close match between the derived analytic expressions and simulation results     

FTN系统中卫星通信QPSK信号的频偏估计研究

本文研究快于奈奎斯特信令(FTN)系统中的无数据辅助的QPSK信号频偏估计方法.相较于奈奎斯特系统,FTN系统的脉冲会叠加的更紧密以此来提高数据速率.据此,将FTN理论应用在卫星通信系统中吸引着众多研究者的目光.然而,由于FTN系统中码间干扰是不可避免的,在接收端准确的估计出频偏变得愈加困难.为了提高估计性能,本文基于接收信号同相与正交分量交叉项与二阶差分项信息,提出一种利用快速傅里叶变换(FFT)估计频偏的方法.仿真结果证明,本文提出的方法可以准确地估计出频偏值.     

基于多通道的跳频信号欠采样频率估计

为实现跳频信号频率跟踪估计,本文提出一种基于多通道的跳频信号欠采样频率估计方法。基于快速傅里叶变换（FFT）,提出了一种3谱线方程的频率校正算法,提高了基于中国余数定理的频率估计方法对短序列信号的频率估计精度,与现有的两种基于离散傅里叶变换（DFT）的频率校正算法相比,序列补零数量灵活。给出了一种频率估计检错机制,可以提高算法可靠性。仿真结果表明,本文所提频率估计算法的精度优于现有算法,增加序列补零数量可进一步提高算法的估计精度和信噪比阈值,降低误差平台;检错机制在-23 dB至8 dB信噪比范围内的准确率高于95.5%。      

基于FFT的正弦信号频率估计综合算法

分析了Rife算法和MJaeobsen算法的性能,指出当信号频率位于量化频率点附近时,Rife算法精度降低,MJacobsen算法精度较高;当信号频率位于两个相邻量化频率点的中心区域时,MJacobsen算法精度降低,Rife算法精度较高。结合这两种算法,提出了一种综合算法。仿真结果表明本算法在整个频段内性能稳定,精度较高,而且计算量较少,容易硬件实现。     

一种适用于高阶QAM信号的改进自恢复均衡算法

本文通过对传统的常模算法进行改进和推广,提出了一种新的常模算法.该算法结合了常模算法优势,利用判决符号的指数幂构成的加权项调整代价函数的模值.在均衡器系数迭代的过程中,可以通过选择权系数,调整MSE的估计值,达到提高算法的稳态性能的目的.理论分析和仿真结果表明,对于高阶的QAM信号来说,在相同的条件下,与常规常模算法相比,提出的算法具有更快的收敛速度和更低的稳态残差;当载波频偏较大时,与多模算法相比,提出的算法仅仅均衡信号的能量,不影响其相位,因此,更适合后端的载波同步处理,得到更好的系统性能.