快速高精度实正弦信号频率估计算法

提出了一种利用信号离散傅里叶变换(DFT)系数的实部或虚部来构造频率修正项的新算法,算法只需傅里叶系数的实部或者虚部的最大值附近的3个DFT系数来构造频率修正项,避免了复数运算从而有效减少了运算量,同时算法的频率估计精度接近CRLB(Cramer-Rao low bound).理论分析和仿真结果证实了方法的有效性.算法简单且具有广泛的适用性.     

基于增强象限的移动站自动定位方法

本文基于增强象限约束提出了一种抑制非直达波定位误差的新方法。该方法首先利用几组相邻的三个基站将服务小区划分为几个不同的增强象限，随后确定移动站的初始象限，然后利用增强象限约束抑制大的非直达波误差，最后对不同时刻的移动站位置进行平滑，进一步减小非直达波误差的影响，并预测下一时刻移动站的象限。该方法不需要知道非直达波误差分布的先验信息，不需要增加系统成本，计算简单，是一种实用的鲁棒性定位方法。理论分析和仿真结果证明了该方法的有效性。     

一种实正弦信号的短时频率估计新方法

针对单频实正弦信号,分析了负频率成分对其频谱分析的影响.提出了一种实正弦信号的短时频率估计新方法.此方法基于把实信号转换为复解析信号的思想,把采样信号与它的90°相移组合成为一个单频复解析信号,然后对此复解析信号再做进一步的频谱分析,从而达到通过消除负频率影响来提高频率估计精度的目的.仿真结果验证了该方法的有效性.     

基于MUSIC的含噪声信号频率估计

频率估计是数字信号处理的重要内容,特别是对含有高斯白噪声的信号进行频率估计一直是信号处理的经典课题。频率估计不仅在理论上,而且在实际应中,都有非常重要的研究价值。本文采用空间谱估计的典型代表MUSIC算法,对含高斯白噪声的信号进行频率估计,同时也通过MATLAB软件对其进行了仿真。仿真结果表明对单、多个含噪声的正弦信号而言,MUSIC算法有良好的频率特性,并能达到预期效果。     

电网谐波分析的频率估计与跟踪

针对多频周期信号推导出一组频率估计公式,并给出了一种电网谐波分析的频率估计与跟踪方法。频率估计公式包括采样序列DFT、相位差计算和频率计算。频率跟踪就是依据前一次频率估计修改下一次采样的采样间隔,从而使同步偏差越来越小。对于电力信号,这种方法能完成实时、高精度的谐波分析,而且计算量非常小。Matlab仿真证实了方法的有效性。     

基于包络线拟合的低频振荡性质在线判别

低频振荡发生时,准确判别低频振荡的类型,对抑制低频振荡、降低其危害具有重要的意义。文中在分析各种机理低频振荡的振荡曲线特征的基础上,提出了基于包络线拟合的振荡性质判别方法。首先,通过经验模态分解(EMD)方法,提取出振荡信号的主导模式振荡曲线,然后通过对提取出的主导模式信号的包络线进行拟合,根据拟合误差判别出振荡的类型。给出了性质判别的流程和实现方法,并通过仿真案例和广域测量系统记录的实际案例,验证了所提出方法的有效性。     

关联RANSAC-DST的FM信号瞬时频率估计

针对冲击-高斯混合噪声环境下的FM信号瞬时频率估计问题,在方向性S变换的基础上,提出了一种基于新型关联随机一致性算法(RANSAC)的瞬时频率估计方法。该算法将原RANSAC算法的随机一致搜索策略与FM信号的物理特征统一起来,构建关联函数以保证在抑制复杂噪声的同时准确跟踪目标信号的时变轨迹。结合方向性S变换的二次平滑特性,算法能够在-7 dB混合噪声的干扰下恢复信号的相位信息。仿真实验在α-高斯混合噪声条件下验证了算法的有效性。     

一种估算调频信号瞬时频率的有效方法

本文提出了通过相位拟合的方法来实现调频信号瞬时频率的估计,对推算原理进行了详细的描述,在计算公式上采用了向量、矩阵的运算形式,为了说明该方法的有效性,针对多种情况进行了仿真试验,取得了理想效果。     

基于自适应陷波器的电网频率估计方法

本文针对电网频率难以精确测量的问题,提出利用自适应陷波器结构的滤波功能,结合电网电压基波信号及其谐波信号的特性,以陷波器实时输出平方值作为陷波器参数的优化目标函数,根据随机优化理论推导出陷波器参数在线迭代算法,从而对与频率有关的陷波参数进行自适应调整,达到电网频率估计的目的。该方法结构简单,通过仿真分析和实验测试,检验了所提出的频率估计算法的收敛速度和逼近精度,表明基于自适应陷波器的电网频率估计方法,可以准确估计出电网频率。     

用于电力系统谐波频率高分辨估计的MUSIC算法

指出了目前电力系统谐波频率常规估计算法的诸多不足,将基于多重信号分类（MUSIC）的高分辨谐波频率估计算法引进电力系统谐波频率估计领域。给出了MUSIC算法的基本原理,对MUSIC算法的频谱分辨能力和频率检测门限进行了理论分析,在Matlab仿真平台下对MUSIC算法和FFT算法的频率估计性能进行了比较。理论分析和Matlab仿真结果表明,MUSIC频率估计算法对数据量要求较低,具有良好的分辨特性和抗噪声能力,且能够检测微弱的谐波信号。     

A frequency response estimation method based on smoothing and thresholding

A standard approach for estimating the frequency function of a linear dynamical system is to use spectral estimation. Traditionally, this is done by smoothing the noisy frequency data using linear filters. The method has proved to be successful in most cases and is widely used. However, if the frequency response has fine details appearing only locally in frequency, the loss of resolution caused by smoothing might result in unacceptable errors. In this paper, a different method for frequency response estimation is suggested. The method utilizes recently proposed wavelet-based denoising schemes combined with traditional smoothing techniques. The wavelet transform is applied in the frequency domain in order to provide a suitable frequency window. Tested through simulations, this approach provides an alternative when traditional methods fail. © 1998 John Wiley & Sons, Ltd.     

电力系统频率响应的改进模型与参数估计

近年来,多种因素导致电力系统频率大波动事故时有发生。而目前对电力系统调频能力预估误差较大,有必要采用电力系统频率响应(SFR)模型计算频率的动态响应。文中分析了SFR经典模型的不足之处,据此改进了SFR模型结构,其中考虑了等值调速器的动态特性。进而提出了SFR改进模型的参数估计方法,先直接计算获得部分参数,然后加入保证稳态一致性的参数约束条件,最后辨识获得其余参数。通过仿真算例对频率响应进行了计算,验证了SFR改进模型结构与参数估计方法的有效性。结果表明,SFR改进模型能够有效表征系统频率响应的主要指标,其精度显著高于SFR经典模型。     

Iterative distributed fault detection and isolation for linear systems based on moving horizon estimation

In modern engineering systems, reliability and safety can be conferred by efficient automatic monitoring and fault detection algorithms, allowing for the early identification and isolation of incipient faults. In case of large-scale and complex systems, scalability issues and computational limitations make centralized monitoring and fault detection methods unapplicable. Research is therefore currently focusing on the development of distributed methods, where the computational complexity is divided among different units. In this paper, we propose a partition-based model-based fault detection and isolation scheme based on moving horizon estimation, able to estimate both the state variables and the possible faults, modeled as additive signals on the state and/or output equations. Its theoretical properties are analyzed, and numerical simulations are performed to witness its potentialities in a benchmark case study.     

Open-circuit voltage-based state of charge estimation of lithium-ion power battery by combining controlled auto-regressive and moving average modeling with feedforward-feedback compensation method

Being one of the important parameters describing the state of power battery, state of charge (SOC) is essential for the electric vehicle battery management system (BMS). SOC estimation method, which combines the constructed controlled auto-regressive and moving average (CARMA) model with the feedforward-feedback compensation method used for revising SOC by the deviation of terminal voltage, is presented in this paper. Fully taken into account the measurement errors of voltage and current, the CARMA model is employed to estimate the battery open-circuit voltage (OCV). With the good consistency of the OCV-SOC curve under the process of battery charge and discharge cycles within a certain temperature range, OCV is adopted to estimate SOC. BP neural network rather than the high order polynomial approximation is used to capture the strong nonlinear relationship between OCV and SOC with the high precision. It is a big challenge for OCV-based SOC estimation that the flat area of OCV-SOC curve for lithium-ion power battery enlarges the measurement errors of OCV. By analyzing the flat characteristic of ΔSOC-OCV curve, the feedforward-feedback compensation for SOC is used for improving the accuracy of OCV-based SOC estimation. Experiment results confirm the effectiveness of the proposed approach that has evidently advantages over other estimation methods.     

SC-FDE系统信道估计与频域均衡算法研究与仿真

信道估计与频域均衡是单载波频域均衡(SC-FDF)系统的两大关键技术.对通信中信道的好坏进行估计,得到信道特征(CSI)是SC-FDE系统进行信道均衡的前提;而信道均衡即通过对估计出的信道衰减特征进行补偿,来减小信号在传输过程中所受外界的影响,信道估计与频域均衡性能的好坏共同决定系统最后均衡的效果.对SC-FDE信道估计和频域均衡技术不同的算法进行分析研究;在此基础上,结合两个模块进行联合仿真,得到性能最优的信道估计和频域均衡组合算法.     

基于FrFT和三次样条插值的瞬时频率估计方法

瞬时频率估计作为非平稳信号分析的主要内容,具有重要的研究意义。针对基于微元法和分数阶傅里叶变换的瞬时频率估计方法在实时性、抗噪性等方面的不足,改用黄金法快速搜索最佳分数阶比以增强其实时性,引入三次样条函数对分段信号中间点频率进行插值以提高其抗噪性。仿真结果表明,本文方法时耗约为现有方法的1/3,在不同信噪比下,本文方法的RMSE和MAE都约为现有方法的1/2,是一种有效的瞬时频率估计方法。     

Robust hybrid estimation and rejection of multi‐frequency signals

We consider the problem of output regulation for LTI systems in the presence of unknown exosystems. The knowledge about the multi‐frequency signals exosystem consists in the maximum number of frequencies and their maximal value. The control scheme relies on two main components: an estimation algorithm, to reconstruct the signal generated by the exosystem, and a controller, to enforce the output regulation property to the closed‐loop system. To tackle the first task, we propose a hybrid observer for the estimation of the (possibly piece‐wise continuous) number and values of the frequencies contained in the exogenous signal. The hybrid observer is particularly appealing for numerical implementations, and it is combined with a self‐tuning algorithm of the free parameters (gains), thus improving its performance even in case of noisy measurements. Semi‐global exponential convergence of the estimation error is provided. As far as the second task is concerned, a robust hybrid regulator is designed for practical rejection of the multi‐frequency disturbance signal acting on the plant. The result is achieved by exploiting the frequencies estimated by the hybrid observer. The effectiveness of the proposed control scheme is shown by means of numerical simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

Parameter estimation for time-delay systems based on the frequency responses and harmonic balance methods

Two parameter estimation methods for linear time-delay systems are proposed based on the frequency responses and the harmonic balance methods. One is the stochastic gradient gradient-based iterative (SG-GI) algorithm and the other is the recursive least squares gradient-based iterative (RLS-GI) algorithm. These two methods can estimate the unknown parameters and the unknown time delays simultaneously by giving sinusoidal signals with different angular frequencies. Furthermore, a comparative study reveals that the RLS-GI algorithm is more effective than the SG-GI algorithm. The effectiveness of the proposed algorithms is illustrated by a numerical example.     

一种计及频率偏移的谐波与邻近间谐波估计方法

新能源大规模并网会诱导电力信号中出现关于基波/谐波对称的邻近间谐波对或单个邻近间谐波。对信号中各频率成分进行参数估计时,往往需要获知邻近间谐波的类型以构建准确的计算模型。而当电网频率偏离额定值时,频谱泄露干扰将使该要求难以实现。为此,本文提出一种在频率偏移时依然有效的邻近间谐波类型判据及基于此判据的谐波与邻近间谐波参数估计方法。首先,通过分析频率偏移与泄露谱线的映射关系,抑制基波与谐波的频谱泄露以提取邻近间谐波谱线;然后,通过对比不同类型邻近间谐波的频谱差异,提出利用谱线比值作为邻近间谐波类型判据;最后,基于邻近间谐波类型信息,构建邻近间谐波谱线方程以精准估计谐波及邻近间谐波参数。本文所提方法在频率偏移时仍能准确判断邻近间谐波的类型,并能实现更精准的参数估计,仿真验证了本文方法的准确性。