Improved phase estimation based on complete bispectrum and modified group delay

In this paper, a new method for extracting the system phase from the bispectrum of the system output has been proposed. This is based on the complete bispectral data computed in the frequency domain and modified group delay. The frequency domain bispectrum computation improves the frequency resolution and the modified group delay reduces the variance preserving the frequency resolution. The use of full bispectral data also reduces the variance as it is used for averaging. For the proposed method at a signal to noise ratio of 5dB, the reduction in root mean square error is in the range of 1.5–7 times over the other methods considered.     

2D-spectral estimation based on DCT and modified magnitude group delay

This paper proposes two new 2D-spectral estimation methods. The 2D-modified magnitude group delay (MMGD) is applied to 2D-discrete Fourier transform (2D-DFT) for the first and to the analytic 2D-discrete Cosine transform for the second. The analytic 2D-DCT preserves the desirable properties of the DCT (like, improved frequency resolution, leakage and detectability) and is realized by a 2D-discrete cosine transform (2D-DCT) and its Hilbert transform. The 2D-MMGD is an extension from 1D to 2D, and it reduces the variance preserving the original frequency resolution of 2D-DFT or 2D-analytic DCT, depending upon to which is applied. The first and the second methods are referred to as DFT-MMGD and DCT-MMGD, respectively. The proposed methods are applied to 2D sinusoids and 2D AR process, associated with Gaussian white noise. The performance of the DCT-MMGD is found to be superior to that of DFT-MMGD in terms of variance, frequency resolution and detectability. The performance of DFT-MMGD and DCT-MMGD is better than that of 2D-LP method even when the signal to noise ratio is low.     

基于经验模态分解重构的二次相关时延估计

针对低信噪比情况下的时延估计,将二次相关( SC)时延估计与经验模态分解( EMD)算法结合,提出了EMD重构二次相关时延估计方法。该方法针对EMD重构时本征模态函数的选择,将倒谱法和谱减法相结合,提出新的本征模态函数中有用信号主导分量和噪声主导分量的区分方案。研究结果表明：EMD重构二次相关法较传统二次相关法抗噪性能更优,更能锐化二次相关峰值;在非高斯有色噪声和高斯白噪声情况下,分别将准确估计时延的信噪比降低了4 dB和2 dB。     

分布式MIMO系统多分量调制信号频率估计

针对分布式多输入多输出系统中的多频偏估计问题进行了研究,提出一种多分量调制信号的高分辨率频率盲估计方法。该方法避免了直接对多分量调制信号进行稀疏表示,无需导频等先验信息,避免传统频率估计方法中的内插、去相位混叠等处理,可一次性精确估计出所有信号频率。通过正定盲源分离方法从接收信号中分离出多个源信号,经过盲去调制处理,将其转换成多单频信号,根据多单频信号的稀疏表示,利用一个随机的压缩矩阵对信号进行压缩,再在压缩域中通过 模优化重构该稀疏信号,获得频率估计。仿真结果表明,与现有算法相比,所提方法可在少数据量、低信噪比下获得高精度估计性能,可在5dB时达到1e-6的平均均方误差。      

LTE中一种基于探测参考信号的信噪比估计算法

为了在上行链路支持频率选择性调度,长期演进(LTE)系统定义了探测参考信号(SRS)用于信道质量估计。该文主要研究SRS的信噪比估计方法,针对Boumard方法和传统DFT方法的缺点,提出一种改进的基于DFT的估计方法。该方法通过在时域修正噪声的估计区间,减小高信噪比时有用信号能量泄露对噪声估计的影响,从而获得更准确的信噪比估计。仿真结果表明,所提方法的估计性能优于Boumard方法和传统的DFT方法,提高了高信噪比时的估计精度,在高信噪比区域,平均估计性能提高了约6 dB以上。     

Zero-crossing based spectral analysis and SVD spectral analysis forformant frequency estimation in noise

The authors discuss a method for spectral analysis of noise corrupted signals using statistical properties of the zero-crossing intervals. It is shown that an initial stage of filter-bank analysis is effective for achieving noise robustness. The technique is compared with currently popular spectral analysis techniques based on singular value decomposition and is found to provide generally better resolution and lower variance at low signal to noise ratios (SNRs). These techniques, along with three established methods and three variations of these method, are further evaluated for their effectiveness for formant frequency estimation of noise corrupted speech. The theoretical results predict and experimental results confirm that the zero-crossing method performs well for estimating low frequencies and hence for first formant frequency estimation in speech at high noise levels (~0 dB SNR). Otherwise, J.A. Cadzow's high performance method (1983) is found to be a close alternative for reliable spectral estimation. As expected the overall performance of all techniques is found to degrade for speech data. The standard autocorrelation-LPC method is found best for clean speech and all methods deteriorate roughly equally in noise     

一种应用于无线传感网的频偏估计改进方法

为解决频偏估计中经典的M&M算法在频偏增大时信噪比门限变差的问题,提出一种改进的频偏估计算法。首先对自相关函数做预平均处理来降低噪声,然后利用预平均值做频偏粗估计,并利用粗估计值纠正相位来减轻相位模糊的问题,最后推导更加合理的窗函数并给出最终频偏估计表达式。仿真表明该算法的信噪比门限比M&M算法至少低-1 dB,且在频偏加大时仍然能保持较低的信噪比门限。在保证-3.5 dB的信噪比门限的前提下该算法的估计范围达到了理论值的90%,另外在最大自相关阶数较小时,估计精度门限优于M&M算法。该算法在M&M算法基础上的改进达到了预期效果,能同时满足无线传感网频偏估计中对低信噪比门限和大估计范围的要求。     

Time delay estimation using the cross bispectrum

The cross bispectrum phase can be effectively used to estimate the time required for a nonGaussian signal to propagate between a pair of spatially separated sensors in the presence of highly correlated Gaussian noise. The authors present a consistent estimator of the phase of the cross bispectrum, derive the exact distribution of the phase of a complex Gaussian sample bispectrum, and show that in most cases the exact distribution can be approximated by a Gaussian distribution. Using this Gaussian approximation, the authors derive the variance of the time delay estimate computed from the sample cross bispectrum of a signal in additive correlated noise. These results allow the performance of time delay estimators based on the cross bispectrum phase to be quantified as a function of the sample size, the skewness of the signal, the signal-to-noise ratio (SNR), and the noise correlation     

提取循环平稳信号特征频率的方法

低阶循环统计量应用广泛,取得了很好的研究成果,但对噪声的抑制效果较差;高阶循环统计量虽能完全抑制高斯噪声的影响,能处理循环平稳、非线性、非高斯过程,但计算量大;循环自相关函数切片谱图能够提取出调制频率,但在较大噪声干扰时效果不明显。为在更低信噪比情况下,采用更快速方法提取出循环平稳信号的特征频率,采用循环双谱的载波频率切片谱提取所需频率。通过Matlab仿真和实验对比研究,发现在信噪比为-15 dB时,循环双谱的载波频率切片谱能直观表达出分析结果。     

无源双基地雷达直达波脉冲丢失与相位突变影响分析

 针对利用天线在方位上机械扫描的脉冲雷达为外辐射源的特殊性,首先分析了发射天线主波束在目标驻留时间内,从其副瓣波束截获的直达波存在脉冲丢失或/和180°相位突变的现象,然后分别推导了互模糊函数峰值输出与脉冲丢失总数、相位突变及其对应脉冲序数间的理论关系,并仿真分析了脉冲丢失或/和相位突变对信噪比损失和多普勒频率估计的影响.由仿真结果发现,脉冲丢失或/和相位突变引入的最大信噪比损失约为4 dB,对应的最大多普勒频率估计误差约为频率分辨单元的0.75倍,且其变化规律与理论分析结果相同.     

基于离散多项式相位变换和分数阶傅里叶变换的加速目标检测算法

 本文提出了一种离散多项式相位变换(DPT)和分数阶傅里叶变换(FRFT)相结合的LFM检测方法.首先,分析了经典DPT算法中调频分辨率与互相关时延、积累脉冲长度以及积累性能之间的相互关系,指出时延较小的DPT算法与经典DPT算法相比,检测性能提高约3dB,但调频率估计误差大.其次,针对这一问题,提出在DPT基础上,利用FRFT进一步提高调频率估计精度,当输入信噪比大于-11dB时,在分数阶域引入一维牛顿迭代法可提高运算速度;最后,给出了算法复杂度和估计误差的理论分析并用实验结果验证了算法的有效性.     

Speech Enhancement Using Phase‐Dependent A Priori SNR Estimator in Log‐Mel Spectral Domain

We propose a novel phase‐based method for single‐channel speech enhancement to extract and enhance the desired signals in noisy environments by utilizing the phase information. In the method, a phase‐dependent a priori signal‐to‐noise ratio (SNR) is estimated in the log‐mel spectral domain to utilize both the magnitude and phase information of input speech signals. The phase‐dependent estimator is incorporated into the conventional magnitude‐based decision‐directed approach that recursively computes the a priori SNR from noisy speech. Additionally, we reduce the performance degradation owing to the one‐frame delay of the estimated phase‐dependent a priori SNR by using a minimum mean square error (MMSE)‐based and maximum a posteriori (MAP)‐based estimator. In our speech enhancement experiments, the proposed phase‐dependent a priori SNR estimator is shown to improve the output SNR by 2.6 dB for both the MMSE‐based and MAP‐based estimator cases as compared to a conventional magnitude‐based estimator.     

测量噪声背景下微弱正弦信号参数估计的互功率谱方法

本文首次把近代谱估计方法引入到互谱估计中，从理论上证明了互相关函数的Ｙｕｌｅ－Ｗａｌｋｅｒ方程，并在此基础上提出了互谱参数谱估计的矩估计方法和Ｌｅｖｉｎｓｏｎ递推估计方法。该方法可以有效地克服传统的互谱ＦＦＴ算法和互周期图法存在的谱分辩率低，谱估计方差大等缺点。文中还给出了信噪比为－３０ｄＢ的正弦信号参数估计的仿真实例。     

针对DTMB-A系统的相位噪声消除算法

相位噪声会破坏OFDM (Orthogonal Frequency Division Multiplex) 符号内频域子载波的正交性,产生公共相位误差（CPE, Common Phase Error）和子载波间干扰（ICI, Inter-Carrier Interference）,对系统性能造成严重影响。针对数字电视地面广播传输标准演进方案（DTMB-A）的相位噪声问题,本文提出了一种两步结合的相位噪声估计和消除算法。首先,利用相邻两帧的帧头符号中所包含的PN（Pseudo Noise）序列,对帧体符号内的公共相位误差进行粗估计;随后,对帧体数据子载波进行标记,选取合适的子载波集合用于估计公共相位误差和子载波间干扰的精确结果。由此获得相位噪声频域估计结果后,通过快速傅立叶变换（FFT, Fast Fourier Transform）得到时域估计结果并进行消除。和现有基于判决反馈的相位噪声估计算法对比,本文所提算法的创新性在于采用了粗估计和精确估计结合的方法,同时利用子载波标记的方法有效降低了由于错误判决导致的误码扩散。仿真结果表明在现有算法已经不能正常工作的情况下,本文所提算法还可以有效的抑制相位噪声对系统性能的影响。      

基于DFT相位的正弦波频率和初相的高精度估计方法

提出一种新的基于DFT相位的正弦波信号频率和初相的高精度估计方法.利用分段DFT频谱的相位差消除了初相对频率估计的影响且避免了相位测量模糊问题.给出了频率和初相估计的均方根误差计算公式.理论分析和Monte Carlo模拟结果显示频率估计均方根误差接近Cramer-Rao(CR)下限,初相估计均方根误差略高于CR下限的2倍.阈值信噪比远远低于基于时域瞬时相位的频率和初相估计方法.在信噪比为6dB、采样点数为1024的情况下,频率估计均方根误差约为DFT频率分辨率的1%,初相估计均方根误差约为2度.该方法已用于FMCW液位测量雷达并取得1mm距离测量精度.     

Parametric SNR Estimation Based on Auto-Regressive Model in AWGN Channels

Signal-to-noise ratio（SNR）estimation for signal which can be modeled by Auto-regressive（AR）process is studied in this paper.First,the conventional frequency domain method is introduced to estimate the SNR for the received signal in additive white Gauss noise（AWGN）channel.Then a parametric SNR estimation algorithm is proposed by taking advantage of the AR model information of the received signal.The simulation results show that the proposed parametric method has better performance than the conventional frequency doma in method in case of AWGN channel.     

The research on channel estimation and signal-noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system

In this paper, the channel estimation and signal-to-noise ratio (SNR) estimation technique of single-carrier frequency domain equalization (SC-FDE) system under low SNR in aeronautical multipath channel are studied, a SNR estimation algorithm which is easy to implement in engineering and an improved LS channel estimation algorithm based on Kalman filter using minimum error entropy (MEE-KF) are proposed. This paper first introduces the SC-FDE system and introduces the principle of MEE-KF, and then, the channel estimation flow based on MEE-KF is obtained by combining it with the traditional LS channel estimation algorithm, which makes the estimation results perform better. Simulation results show that after getting more accurate noise variance, the channel estimation results can better follow the changes of the channel after MEE-KF processing, so as to resist the doppler frequency offset effect and make the channel estimation results more accurate, that is the channel response results of the data part can be closer to the real situation, so that the communication performance of SC-FDE system has also been greatly improved.     

基于子阵近场零陷权的联合波达方向估计方法

针对海底长线阵在近场辐射声干扰及空间水平非均匀噪声下的远距离估计目标波达方向 (DoA)问题,该文提出一种基于长线阵分子阵近场零陷权的联合目标方位估计方法。该方法将长线阵分解为多个高重叠子阵,对各个子阵利用零陷抑制技术去除近场强干扰对目标探测的影响,再利用各子阵对远距离目标方位估计结果差异性小、非目标所在频率即噪声对应空间谱最大值随机的特点,空间频率方差加权综合各子阵的目标方位估计结果,从而抑制空间非均匀噪声,实现对远距离目标的探测。仿真结果表明,与长线阵常规波束形成、长线阵近场零陷常规波束形成、长线阵近场零陷传统多重信号分类方法相比,该文方法能够有效降低空间谱背景级60 dB以上,输出信噪比提高15 dB以上,具有较强的提高信噪比能力及较高的空间分辨力,因此具有较好的工程应用价值。     

OFDM系统中基于SNR估计的改进DFT信道估计算法

为提高目前无线通信系统中正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术下的信道估计性能,分析了基于离散傅里叶变换(Discrete Fourier Transform,DFT)的信道估计算法存在的缺陷.针对传统DFT信道估计算法没有考虑循环前缀内噪声的...     

一种基于序列相关的信噪比估计算法

针对多径信道,提出了一种基于序列相关的信噪比估计算法,利用本地序列与接收信号相关,并采用最小二乘估计法,精确地估计了接收信号幅度和噪声方差,得到了两径信道下信噪比的估计值。仿真结果表明该算法整体估计性能较好,特别适合于低信噪比条件下。在信噪比为-1dB时,与现有的频域和二阶矩四阶矩（M2M4,2-order and 4-order Moments）估计算法相比,该算法的归一化均方误差分别降低了0．09和0．2。