频率估计的一种多段同频等长信号频谱融合法

为提高信号频率估计精度和现有方法的普适性,提出一种基于频谱融合的多段同频等长信号的频率估计算法。设计相位差补偿因子克服分段信号相位不连续问题,以达到相位连续信号的频谱分析效果;建立搜索频率序列修正相位差补偿因子中的未知参数,并对分段信号频谱进行相位差补偿得到修正频谱矩阵;通过累积频谱抽取谱和修正频谱计算频谱相关序列并搜索最大值,其对应搜索频率即为该算法的频率估计值。数值仿真实验表明,基于该算法频率估计的均方根误差约为现有方法的1/4~2/3,较为接近Cramer-Rao下限。     

数字测频算法研究综述

介绍了目前比较常用的几种数字测频算法及其基本原理,并对其中的直接计数法、相位推算法、频率推算法、傅里叶变换法及谱估计等方法进行了MATLAB仿真研究.总结了各种算法的主要优缺点,为设计者选取合适的算法进行工程应用提供了参考.     

频率选择性衰落信道下OFDM信噪比盲估计

针对频率选择性衰落信道下带有载波频偏的OFDM(正交频分复用)信号信噪比(SNR)估计问题,提出一种基于空载波OFDM系统的SNR盲估计方法.由于本振和接收信号之间的不一致,会使得接收到的信号带有一定的频偏.频偏的存在破坏了子载波间的正交性,增加了子载波间的干扰噪声,从而减少了SNR.首先分析了频偏对信噪比的影响并得到有无频偏时信噪比之间的关系,其次根据空载波的特点估计出无频偏时的信噪比,再基于上述关系对OFDM信号进行有频偏时的信噪比盲估计,最后通过仿真验证了理论分析的正确性.     

宽带混合信号的快速DOA估计算法

针对均匀线列阵,在宽带混合信号(不相关和相干信号共存)情形下,提出了一种DOA快速估计新算法。利用阵列协方差矩阵的Hermitian性,通过酉变换将各频点的复数据矩阵映射为实矩阵,通过实值化的TOFS法先直接估计出宽带非相关信号的DOA;然后利用空间差分技术,在各个频点上得到只含相干信号的数据协方差矩阵;通过Toeplitz矩阵重构,在不降低阵列孔径的条件下,可实现相干信号的解相干,再利用实值TOFS法可得到相干信号的DOA。由于算法是并行分别对不相关和相干信号进行DOA估计,在信源过载(信号数大于阵元数)的情形下,算法依然有效,同时由于实值化,算法的计算复杂度较小。仿真结果验证了算法的有效性。     

基于改进WVD的跳频信号参数估计方法

为了克服传统的平滑伪魏格纳分布(SPWVD)在跳频信号参数估计中分辨率降低的问题,提出基于改进WVD算法的跳频信号参数估计新方法。通过分析跳频信号WVD的性质和特点,构造出与跳频信号WVD自项支撑区重合的时频窗,用其与信号WVD相乘进行加窗,有效抑制交叉干扰项的同时保持了WVD良好的时频分辨率,得到了清晰的跳频信号时频分布,基于此分布给出跳频信号参数估计的具体步骤。仿真实验结果表明,该方法有效可行且具有很好的整体性能。     

一种基于功率谱估计的盲载频估计新算法

信号载波频率估计是通信、雷达、声纳以及电子对抗等领域信号处理中的一个重要问题,将经典的载频估计算法——频率居中法与Welch功率谱估计算法相结合,提出一种改进的盲载频估计新算法。该算法无须信号的调制类别和定时信息即可实现信号的盲载频估计,在短波信道的仿真环境下,其低信噪比下的估计性能要优于频率居中法。即使在恶劣的短波信道环境下,该算法仍可实现对载频较为精确的估计,在短波通信中有着良好的应用前景。     

基于听觉外围模型的音频基频估计方法

针对音频信号中的暂态成分对基频检测可靠性的影响,提出了一种基于听觉外围模型的基频估计方法。该方法根据听觉外围模型来模拟声音在人耳内耳听觉神经上传导过程,并利用循环平均幅度差函数判断每个神经传导信号上呈现的时域周期性,进而提取音频信号的基频。实验结果表明,在纯净音频条件下,该方法能准确地估计出音频信号的基频,并且在不同音量打击乐信号的干扰下,所提方法的平均错误率低于三种参考方法。     

Direct synthesis of pseudo-random ternary perturbation signals with harmonic multiples of two and three suppressed

This paper proposes an analytical method to directly synthesise pseudo-random ternary perturbation signals for the identification of frequency response functions, through the multiplication of two components signals which satisfy a prescribed set of properties. The ternary signals generated have harmonic multiples of two and three suppressed; this specification is useful for reducing the effects of nonlinear distortion on the linear estimate. The signals have uniform magnitude in all, except two, of the nonzero harmonics. The method is significant in overcoming the existing problem of sparsity in the available periods when analytical methods are used, as well as the relatively long computational time required in approaches based on exhaustive search or computer optimisation. The proposed technique presents a breakthrough as it eliminates the sequence-to-signal conversion stage required in the existing conventional methods. A direct consequence is the increased signal power within amplitude constraints, which now equals the theoretical limit for the specification considered. If it is necessary to further increase the number of available periods, the mathematical derivation can be extended to a class of suboptimal direct synthesis signals; however, these possess reduced signal power compared with direct synthesis signals.     

一种低复杂度的载波偏移估计算法

针对载波偏移引起OFDM系统的严重子载波干扰和性能下降这一问题,提出一种在承载数据子载波中间插入不承载数据的子载波的算法,算法是通过从时域OFDM符号的前半部分和后半部分的相位差获取频率偏移的信息来估计频偏的。这种算法不仅计算复杂度较低,而且估计准确,在多径信道条件下频偏校正后系统的性能能基本接近信道理想估计条件下的误比特率。     

不同特征数字信号的谱估计算法性能分析

通过实验八种经典和现代的数字信号谱估计算法,并分析了这几种谱估计算法对不同特性信号主要包括周期信号、声音信号和随机信号的影响和差异,从这些算法所表现出的特征和差异中得出针对不同特征信号的谱估计算法性能的优劣性.     

基于EMD瞬时频率估计在电力系统中的应用

于经验模式分解（Empirical Mode Decomposition,EMD）瞬时频率估计是一种新的时频分析方法,它具有良好的时频局部化特征,适用于电力系统故障分析。它是通过EMD方法提取非平稳信号的本征模态函数（Intrinsic Mode Function,IMF）,再进行Hilbert变换即可得到各信号分量的瞬时频率,对其进行分析即可检测到信号发生故障和扰动的准确时刻。此方法从根本上摆脱了傅立叶分析的局限性,通过对中性点不接地系统中由单相接地故障激发铁磁谐振的仿真,验证了此方法的有效性。     

基于周期信号的频域检测方法研究

在分析周期信号尤其是多频周期信号时,为了得到正确的分析结果,除考虑叠加测量噪声模型及其对测量结果的影响之外,还必须考虑由于时域的离散化而可能造成的频域混叠现象,以及由于采样过程记录的信号样点序列长度有限而可能造成的频谱泄漏现象.因此,在基本矩形窗函数频域检测方法的基础上,对Blackman窗函数的频域检测方法进行了研究.该方法对被测信号在时域加Blackman窗函数,在频域实行内插,可以有效地减小检测过程中信号的频谱泄漏,从而得到精确的测量结果,实验结果证明了该方法在周期信号检测过程中的有效性和先进性.     

Application of multi-level signals to the identification of direction-dependent processes

Theoretical results for the output and the input-output crosscorrelation function are derived for first order direction-dependent processes perturbed using pseudo-random maximum length ternary (MLT) signals with unsymmetrical signal levels. The analytical results are valid if the process output is either always increasing or always decreasing when the input is at its median level of zero. It is shown that, although this is not normally the case for the whole of the signal period, good approximations to the analytical results are obtained when it is the case for most of the signal period, as can be achieved with a suitable choice of signal levels. MLT signals with unequal spacing between signal levels can also be used to minimise the nonlinear distortion. This is equivalent to compensating for the direction-dependent behaviour of the system by preceding it with a static nonlinearity. Based on the theoretical and simulation results obtained, a novel technique is proposed to allow the best linear approximation of the process to be estimated from the ratio between the amount of time when the output increases to that when it decreases. The proposed method is shown to be applicable even when the number of signal levels is greater than three, and is less susceptible to the effects of noise than the method of correlation analysis and least squares.     

Local identifiability of time-invariant linear systems by periodic test signals

This paper is concerned with the parameter local identifiability of dynamic systems operating in periodic regimes. The systems dealt with are time-invariant and discrete-time linear systems, with an output white gaussian disturbance. Sets of frequencies are characterized such that the parameter vector is identifiable if and only if the spectrum of the periodic test signal does not vanish over one of these sets. The analysis is developed by taking also into consideration measurement schedule sets which are scattered along the time axis.     

Scaling analysis of baseline dual-axis cervical accelerometry signals

Dual-axis cervical accelerometry is an emerging approach for the assessment of swallowing difficulties. However, the baseline signals, i.e., vibration signals with only quiet breathing or apnea but without swallowing, are not well understood. In particular, to comprehend the contaminant effects of head motion on cervical accelerometry, we need to study the scaling behavior of these baseline signals. Dual-axis accelerometry data were collected from 50 healthy adult participants under conditions of quiet breathing, apnea and selected head motions, all in the absence of swallowing. The denoised cervical vibrations were subjected to detrended fluctuation analysis with empirically determined first-order detrending. Strong persistence was identified in cervical vibration signals in both anterior-posterior (A-P) and superior-inferior (S-I) directions, under all the above experimental conditions. Vibrations in the A-P axes exhibited stronger correlations than those in the S-I axes, possibly as a result of axis-specific effects of vasomotion. In both axes, stronger correlations were found in the presence of head motion than without, suggesting that head movement significantly impacts baseline cervical accelerometry. No gender or age effects were found on statistical persistence of either vibration axes. Future developments of cervical accelerometry-based medical devices should actively mitigate the effects of head movement.     

基于频域ICA的波达方向估计方法

为降低阵元数目和提高相干多径入射信号的波达方向(DOA)估计精度。提出了一种基于频域独立分量分析与波束零点形成相结合的DOA估计方法。该方法综合利用阵列结构信息和目标信号的统计独立特性,与常规算法相比,降低了算法对阵元数目和精度的依赖,并能实现对相干多径入射信号的DOA估计。计算机仿真结果表明,该算法具有少阵元、收敛快、误差小的特点。     

A new parametric frequency-wavenumber spectrum estimation algorithm and its application to the analysis of 3-dimensional epicardial ECG signals

This paper presents a 3-dimensional (3-D) frequency-wavenumber spectrum estimation (FWSE) approach to the analysis of ECG signals. This approach treats the data as ‘wavefronts plus noise’ and provides a means of estimating key parameters associated with propagating wavefronts. A high resolution technique based on minimum variance representations of 3-D data fields (3-D CLS technique) is employed to obtain the FWSE. Computer simulation results that demonstrate the high resolution property of the technique when compared with the maximum-likelihood method of Capon are presented. Results of application of the technique to epicardial ECG data collected from a sensor array are also presented and discussed.     

改进的DSSS电磁波随钻测量信号载频估计算法

为了解决随钻测量中电磁波信号的载频估计问题,基于直接序列扩频（ DSSS）通信原理,建立了改进的电磁波信号载频估计法,该方法采用信号自适应干扰对消技术滤除噪声信号,然后再通过带通滤波技术获得DSSS信号的频带,从而提高了信号的信噪比（ SNR）。在此基础上,建立了System View仿真模型,仿真结果表明：改进的载频估计法可以有效滤除噪声信号,精确地检测出电磁波信号的载波频率。     

Frequency estimation of undamped exponential signals using genetic algorithms

In this paper, we consider the problem of frequency estimation of undamped superimposed exponential signals model. We propose two iterative techniques of frequency estimation using genetic algorithms. The proposed methods use an elitism based generational genetic algorithm for obtaining the least squares and the approximate least squares estimates. In the simulation studies, it is observed that the proposed methods give nearly efficient estimates, having mean square error almost attaining the corresponding Cramér-Rao lower bound. The proposed methods significantly do not depend on the initial guess values otherwise required for other iterative methods of frequency estimation. It is also observed that the proposed methods have fairly high breakdown point with respect to different types of outliers present in the data. Outlier robustness and accuracy of the proposed methods are compared with the classical approaches for this problem.