强背景噪声环境下的线性调频信号频率估计

估计信号的瞬时频率常用Cohen类时频分布的时间一阶条件矩，但这些方法在更低信噪比下存在较大的估计方差。基于线性调频信号的自相关和互相关可以实现噪声压缩的结论，提出了改进的基于互Wigner-Ville分布线性调频信号的频率估计方法。该方法具有更强的抗噪声能力，在多元信号频率估计时，抑制了交叉项的影响。仿真实验的结果证明了算法的有效性。     

低信噪比情况下调频信号的瞬时频率估计

提出一种基于互Wigner-Ville分布(XWVD)的瞬时频率迭代估计方法.理论分析了该方法的收敛性,通过仿真比较了各种瞬时频率估计方法在噪声下的估计方差,证明此方法在低信噪比情况下对估计线性调频信号的瞬时频率有较好的效果.并采用加窗的方法改进了此算法,仿真结果证明,改进的方法对非线性调频信号的瞬时频率进行了有效估计.     

STTFD的特性分析及其在线性调频信号 参数估计中的应用

 精确地估计线性调频(LFM)信号的中心频率和调频率值,在雷达信号处理中有着十分重要的作用.WVD变换具有估计线性调频信号的中心频率和调频率特性,但当存在多个线性调频分量时,交叉项会严重影响线性调频信号中心频率和调频率的估计.针对这一问题,本文提出了基于STTFD(时频分布尺度变换)的线性调频信号参数估计的方法,即在时频平面内对信号进行尺度变换,去除信号瞬时时间和相关函数延迟量的耦合,使线性调频信号的频率随时间变化呈线性分布变为不随时间变化的常数分布,再通过在时频平面内沿时间轴做FFT积累所得到的信号峰值位置来估计信号的中心频率和调频率参数值,并且对STFD的特性以及相关函数延迟量和尺度变换常数对STTFD的影响进行了详细的分析.在本文最后,通过仿真数据验证了STTFD的特性及其精确估计线性调频信号参数的有效性.     

强背景噪声环境下的线性调频信号检测

基于线性调频(LFM)信号Wigner-Ville变换的零频处仍保存原信号所有信息的结论，提出了改进的基于互Wigner-Ville分布线性调频信号的检测方法。该方法具有较好的抗噪声能力，在更低的信噪比下，可以实现单个或多个强度相差较大的线性调频信号的检测。仿真实验的结果证明了算法的有效性。     

基于频率区间二分解调的LFM信号参数估计方法

首先讨论了线性调频信号在时频域的主要特点及调频斜率与振幅频谱的关系,在此基础上提出基于频率区间二分解调的LFM信号参数估计方法。该方法充分利用了LFM信号的线性性质,有效地将信号与噪声分离开来,通过二分法搜索调频斜率,提高了LFM信号参数的估计效率。     

基于尺度变换的宽带线性调频信号时差/尺度差估计算法

提出了一种基于尺度变换的宽带线性调频信号时差和尺度差的快速算法.根据两路接收到的线性调频信号间调频率之比为尺度差的平方的特点,利用分数阶傅里叶变换分别估计出两路信号的调频率,即可获得尺度差的估计.将估计的尺度差对一路信号进行伸缩,并计算伸缩后信号与另一接收信号的时域相关,根据相关峰的位置估计出时差.相比于传统基于宽带互模糊函数的方法,该方法避免了二维搜索宽带互模糊函数的峰值,只需若干次快速傅里叶变换即可实现,能够显著降低运算量.仿真结果显示该方法在高信噪比下逐渐接近克拉美-罗下界.     

基于互Wigner-Ville分布的到达角估计

研究了对线性调频信号的到达角估计;提出了基于互Wigner-Ville分布(XWVD)估计信号到达角的方法.通过时频分布,在时频面上进行信号预分选;根据XWVD时频脊点上的相位获得信号时延,从而获得信号到达角.该算法可实现多信号分辨,也可实现对时变频率信号的到达角估计.计算机仿真结果证实了该算法的有效性.     

基于瞬时自相关算法的线性调频雷达信号脉内分析研究

估计线性调频信号的瞬时频率和调制参数,是进一步获得脉内特征并最终识别信号的基础。线性调频信号模型由软件编程产生,引入瑞利分布高斯谱模型来模拟背景杂波。提出采用小波包分析方法进行消噪处理,以瞬时自相关算法估计信号的瞬时频率,进而求出调制参数。瞬时自相关算法进行了滑动平均改进。计算机仿真实验得到瞬时自相关算法估计瞬时频率的...     

应用WVD估计AM-FM信号的瞬时频率

该文研究了应用WVD谱峰检测估计AM-FM信号的瞬时频率的方法及其性能。理论分析表明;对线性调频的AM-FM信号,只要其幅度的WVD在频率为零处取得最大值在任意时刻都成立,则基于WVD谱峰检测得到的瞬时频率估计是无偏的,并给出了估计的方差。仿真实验使用高斯包络的线性调频信号表明,利用WVD可以有效地估计AM-FM信号的瞬时频率。     

基于欠采样的宽带线性调频信号参数估计

基于中国余数定理解频率模糊和解线调方法,提出一种无模糊欠采样的宽带线性调频信号的调频斜率和初始频率的估计算法.首先,欠采样宽带线性调频信号与其两路不同延迟共轭相乘,根据两路输出信号的单频特性,利用FFT、谱峰检测(PSD)和中国余数定理进行宽带线性调频信号的调制斜率无模糊估计;其次,根据估计的调制斜率数字合成无载波的线性调频信号对另外两路不同延迟的欠采样宽带线性调频信号解线调处理,利用类似方法进行宽带线性调频信号的初始频率无模糊估计.利用频谱细化技术,参数估计精度可进一步提高.计算机仿真证实了算法的有效性.     

Viterbi algorithm for chirp-rate and instantaneous frequency estimation

An instance of the Viterbi algorithm has been applied to the cubic phase function and chirp-rate estimation. The proposed algorithm has shown excellent performance for high noise environment. The obtained chirp-rate estimate is used in the instantaneous frequency estimation. The proposed instantaneous frequency estimator gives superior performance with respect to the state-of-the-art techniques for signals with non-linear instantaneous frequency.     

基于局域波的非参数瞬时频率估计

对于频率缓变的单一分量信号叠加噪声的情况,根据其瞬时频率中真实瞬时频率占主导趋势的特点,先使用平滑相位差分法——极大似然法估计噪声信号的瞬时频率,用局域波分解法求极大似然法估计瞬时频率的趋势项,从而得到与理论瞬时频率相符的结果,与其他的瞬时频率估计方法相比,本方法具有精度高、计算量小的优点.     

改进的相位展开算法及其在瞬时频率估计中的应用

 研究了一种改进的相位展开算法及其在瞬时频率估计中的应用.首先讨论了噪声对相位展开的影响,发现当每个周期内的样本数为2个样本时相位展开具有最佳的性能;接着利用这个性质得到一种简单的相位展开算法,可以在较低信噪比条件下估计出信号的瞬时相位;随后把相位展开算法应用于正弦波频率估计,得到了改进的相位平均法,利用它可以在较低信噪比条件下得到宽带信号的瞬时频率曲线;最后通过MATLAB仿真对算法进行验证.     

Signal enhancement by time-frequency peak filtering

Time-frequency peak filtering (TFPF) allows the reconstruction of signals from observations corrupted by additive noise by encoding the noisy signal as the instantaneous frequency (IF) of a frequency modulated (FM) analytic signal. IF estimation is then performed on the analytic signal using the peak of a time-frequency distribution (TFD) to recover the filtered signal. This method is biased when the peak of the Wigner-Ville distribution (WVD) is used to estimate the encoded signal's instantaneous frequency. We characterize a class of signals for which the method implemented using the pseudo WVD is approximately unbiased. This class contains deterministic bandlimited nonstationary multicomponent signals in additive white Gaussian noise (WGN). We then derive the pseudo WVD window length that gives a reduced bias when TFPF is used for signals from this class. Testing of the method on both synthetic and real life newborn electroencephalogram (EEG) signals shows clean recovery of the signals in noise level down to a signal-to-noise ratio (SNR) of -9 dB.     

Nonparametric estimation of instantaneous frequency

The local polynomial approximation of time-varying phase is used in order to estimate the instantaneous frequency and its derivatives for a complex-valued harmonic signal given by discrete-time observations with a noise. The considered estimators are high-order nonparametric generalizations of the short-time Fourier transform and the Wigner-Ville distribution. The asymptotic variance and bias of the estimates are obtained     

Fatigue estimation with a multivariable myoelectric mapping function

A novel approach to muscle fatigue assessment is proposed. A function is used to map multiple myoelectric parameters representing segments of myoelectric data to a fatigue estimate for that segment. An artificial neural network is used to tune the mapping function and time-domain features are used as inputs. Two fatigue tests were conducted on five participants in each of static, cyclic and random conditions. The function was tuned with one data set and tested on the other. Performance was evaluated based on a signal to noise metric which compared variability due to fatigue factors with variability due to nonfatiguing factors. Signal to noise ratios for the mapping function ranged from 7.89 under random conditions to 9.69 under static conditions compared to 3.34-6.74 for mean frequency and 2.12-2.63 for instantaneous mean frequency indicating that the mapping function tracks the myoelectric manifestations of fatigue better than either mean frequency or instantaneous mean frequency under all three contraction conditions.     

The Wigner distribution of noisy signals with adaptivetime-frequency varying window

Time-frequency representations using the Wigner distribution (WD) may be significantly obscured by the noise in the observations. The analysis performed for the WD of discrete-time noisy signals shows that this time-frequency representation can be optimized by the appropriate choice of the window length. However, the practical value of this analysis is not significant because the optimization requires knowledge of the bias, which depends on the unknown derivatives of the WD. A simple adaptive algorithm for the efficient time-frequency representation of noisy signals is developed in this paper. The algorithm uses only the noisy estimate of the WD and the analytical formula for the variance of this estimate. The quality of this adaptive algorithm is close to the one that could be achieved by the algorithm with the optimal window length, provided that the WD derivatives were known in advance. The proposed algorithm is based on the idea that has been developed in our previous work for the instantaneous frequency (IF) estimation. Here, a direct addressing to the WD itself, rather than to the instantaneous frequency, resulted in a time and frequency varying window length and showed that the assumption of small noise and bias is no longer necessary. A simplified version of the algorithm, using only two different window lengths, is presented. It is shown that the procedure developed for the adaptive window length selection can be generalized for application on multicomponent signals with any distribution from the Cohen (1989, 1990, 1992) class. Simulations show that the developed algorithms are efficient, even for a very low value of the signal-to-noise ratio     

结合时变滤波和时频掩码的语音增强方法

本文提出了一种结合鲁棒时变滤波和时频掩码的语音增强方法。首先在带噪语音的时频域中,结合图像处理方法估计出初始瞬时频率信息。然后基于该瞬时频率信息,利用鲁棒时变滤波算法构建降噪后的语音信号。最后根据重构语音的时频特征预测时频掩码。该掩码在带噪语音的时频域中能够有效地保留语音成分且抑制噪声成分,从而达到语音增强的目的。实验结果表明,在几种常见背景噪声环境下,所提语音增强算法在抑制背景噪声干扰、提升语音整体质量方面表现良好,尤其是在低信噪比环境下具有明显的优势。      

Statistical properties of the instantaneous frequency for a noisy signal

In this paper a comprehensive study of the statistical properties of the instantaneous frequency is presented. A rather crude estimate is given in the both situation where the signal to noise ratio tends respectively towards zero or infinity. For an intermediate state a more refined and exact computation, which recovers the asymptotic situations, has been performed. Two main results must be emphasized; the first deals with the bias of the instantaneous frequency and the second with the good immunity of this frequency against the noise.