基于谱相关分析的频谱空洞检测方案

设计了一种新的频谱空洞的检测方法,基于谱相关分析的理论,在循环相关匹配滤波器的基础上,采用单通道信号的检测统计量作为统计判据,用Bartlett(巴特利特)窗周期图法进行功率谱估计,并进行了蒙特卡罗仿真.仿真结果表明,在低信噪比的情况下,该检测方案具有良好的检测性能.     

多用户DS-UWB信号的伪码周期估计*

在单用户直接序列超宽带(DS-UWB)信号的伪码(PN)周期估计的基础上,采用信号功率谱二次处理的方法,实现了多用户DS-UWB信号的PN码周期盲估计。该方法对接收信号的功率谱进行二次谱处理,最后得到的二次谱就会在接收的多用户DS-UWB 信号的PN码周期整数倍处出现一系列的尖峰脉冲,通过检测这些脉冲的间距就可以得到PN码周期的估计。通过理论推导表明了该方法的可行性,利用计算机仿真,验证了多用户DS-UWB信号在PN码周期的整数倍确实存在二次功率谱的脉冲串,这些脉冲串还具有类似高斯脉冲二次功率谱的形状。同     

一种基于非周期随机共振的微弱信号检测方法

随机共振滤波器能够在强噪声背景中跟踪微弱信号(非周期或周期信号)波形,并将幅度放大,这正好弥补了匹配滤波器在强噪声背景下检测性能的严重不足。本文给出了FHN随机共振的简化模型及计算方法,在深入分析FHN随机共振模型参数对其滤波性能影响的基础上,结合随机共振滤波器和匹配滤波器,提出了一种基于FHN随机共振模型检测确知信号的方法。首先将接收信号经FHN随机共振滤波器进行滤波,再进行匹配滤波,最后将滤波结果和门限进行比较判断信号是否存在。经过实验验证,该方法具有较好的效果。     

Kalman滤波在Yule-Walker谱估计中的应用

在现代谱估计中,由于Yule-Walker沃克谱估计算法中平稳随机序列的长度n在某些情况下偏小,使计算出的ARMA随机过程的功率谱密度不能精确逼近真实值,所以我们在用自相关法估计AR模型参数时加入了kalman滤波器。将估计的AR模型系数及高斯白噪声作为滤波器的输入及部分参数,对最终估计的功率谱进行修正。实验结果表明,...     

WCDMA信号检测与参数估计

针对低信噪比下WCDMA信号检测与伪码(OVSF码)周期检测的难题,利用四阶累积量能够有效抑制高斯白噪声和二次谱具有明显谱峰的特性,提出了一种基于四阶累积量和二次谱相结合的WCDMA信号盲检测方法。该方法首先利用四阶累积量的切片检测出WCDMA信号,并估计得到WCDMA信号的采样率,接着通过二次谱算法所得到的谱峰间的距离来估计出OVSF码的周期参数。计算机仿真结果表明,该算法可以有效地对WCDMA信号进行检测并估计OVSF码周期。     

基于小波周期图的功率谱估计算法研究

作为一种功率谱的估计方法,周期图法具有物理概念清晰、直观、计算方便的优点。由于傅里叶变换的一些局限性,一直以来,经典周期图估计法不能很好的处理非平稳信号,并且缺乏很好地处理分辨率与方差的方法。文章在小波理论的基础上,结合经典周期图,深入阐述了小波周期图的基本算法与相关理论。通过matlab仿真分析表明,小波周期图有效地在各个不同的尺度上对信号的功率谱进行局部估计。     

非白高斯噪声中基于导频的匹配滤波频谱检测

为了在低信噪比的情况下,能够用很少的采样样本得到很高的检测概率,考虑到现实生活中噪声和信号在传输过程中的衰落,所以在非白高斯信道中采用线性模型对信号进行估计,在此基础上对导频运用匹配滤波检测,讨论了决定检测概率的重要因素——偏移系数的最大值的选取。仿真结果表明,选取非白高斯噪声信道是必要的;偏移系数选取最优值将会得到很好的检测性能;对导频进行检测可以减少采样数。     

非高斯噪声下Kalman滤波熵理论算法研究

从一个新的角度结合具体的算法讲述了Kalman滤波器的原理,并对噪声为非高斯情况下结合熵的理论提出了假设,解决了噪声为非高斯情形下的滤波器设计的瓶颈。传统的Kalman滤波器是在噪声为高斯的情形下得出的最优滤波估计,但是现实生活中大多数噪声却是未知的、不确定性并且非高斯的。为了清楚说明熵原理应用于非高斯滤波器的设计结果,运用了数学统计的方法,对比滤波效果,说明了其可行性,证明了这种方法更适应于对噪声情况未知、参数不明确的情况,为研究广义噪声的随机系统提出了一种新的通用的解决途径。     

非高斯噪声下Kalman滤波熵理论算法研究

从一个新的角度结合具体的算法讲述了Kalman滤波器的原理,并对噪声为非高斯情况下结合熵的理论提出了假设,解决了噪声为非高斯情形下的滤波器设计的瓶颈.传统的Kalman滤波器是在噪声为高斯的情形下得出的最优滤波估计,但是现实生活中大多数噪声却是未知的、不确定性并且非高斯的.为了清楚说明熵原理应用于非高斯滤波器的设计结果,运用了数学统计的方法,对比滤波效果,说明了其可行性,证明了这种方法更适应于对噪声情况未知、参数不明确的情况,为研究广义噪声的随机系统提出了一种新的通用的解决途径.     

相位匹配噪声估计的高阶谱去噪方法

大多数去噪方法只能对高斯噪声或某一类有色噪声进行去噪处理.提出一种新的相位匹配噪声估计的高阶谱去噪方法.利用该方法既可以去除高斯噪声又可以去除非高斯噪声,通过高阶谱和相位匹配实时的逼近当前噪声,建立二次去除噪声方法,通过实验证明该方法能够非常明显的去除高斯与非高斯噪声,在无法分出噪声的种类情况下进行信号的去噪,取得非常好的去噪效果.     

Spectral analysis of atmospheric radar signal using filter banks — polyphase approach

This paper proposes a new non-parametric method to estimate the power spectral density of atmospheric radar signals using uniform filter banks through polyphase approach. The performance of proposed method is investigated for a simulated broadband and narrowband signals. This method reduces the variance without affecting the resolution and improves the signal to noise ratio significantly when compared to the existing method (periodogram/modified periodogram). The variance reduction is observed to be more in case of narrowband signals. The method has the computational cost similar to modified periodogram approach. This method is tested for practical atmospheric data collected at NARL, Gadanki, India, through the mesosphere–stratosphere–troposphere (MST) radar, back scattered echoes, in particular from high altitudes, which has low signal to noise ratio. Results have been validated using simultaneous Global Positioning System (GPS) Sonde data.     

An adaptive signal-to-noise ratio estimator in mobile communication channels

Representing the reception condition directly, signal-to-noise ratio (SNR) is an important parameter in mobile propagation channels, and therefore is widely used in system performance evaluations and adaptive applications. Hence, this paper puts forward a frequency domain SNR estimator in mobile communications, where we exploit the signal model with the band-limited fading channel and the additive white Gaussian noise. With the above model, the noise power spectrum density can be estimated from the periodogram of channel-plus-noise signals, subsequently leading to our SNR estimation. Moreover, in order to degrade the intrinsic spectrum leakage of fast Fourier transform in periodogram calculation, the leakage expression is derived analytically and then an adaptive process is proposed to make a tradeoff between leakage reduction and noise smoothing. We verify our algorithm by simulations and observe high accuracy in a wide range of velocities and SNRs. Additionally, unlike the conventional work, the proposed estimator is not strictly based on the assumption of specific Doppler spectral shapes except for the requirement of the band-limited channel, hence it is robust to general mobile channels.     

随机振动多窗口谱分析法模型建立及统计分析

针对随机振动中谱估计算法,分析了周期图估计算法对噪声系列的功率谱相关系数及加窗造成的信息损失,在此基础上分析了由直接谱估计算法构建的多窗口谱分析法,建立了其噪声模型,推导了估计方差减小与参与运算的窗口数的关系。针对白噪声序列,得到MTSA估计器避免加窗而造成信息损失时窗口数与信号序列的关系,最后推出了MTSA估计器的统计特征。     

混沌背景中微弱网络传输信号有效检测仿真

针对传统微弱信号检测方法存在检测准确性较低、检测时间较长等缺点,提出混沌背景中微弱网络传输信号有效检测方法。根据Wiener-Khinchine定理对信号函数计算,并经过傅里叶变换获得信号的自相关函数与其相对应的功率谱,利用周期图法分析获得微弱信号的检测原理,运用Briot-Bouquet引理进行计算,根据计算结果证明瞬态信号以及周期信号的存在,并以此为基础构建混沌背景下噪声的检测模型,从预测误差中检测出在噪声层下的微弱网络传输信号。仿真结果表明,所提方法能够快速检测出在混沌背景下的微弱信号,且检测时间较短、检测误差较低,可广泛引用在现实生活中。     

一种改进的有色噪声背景下信号的检测算法

摘要:对于自回归型(AR)的广义平稳(WSS)高斯有色噪声,以改进的协方差法得到了该噪声未知参数基于AR模型的估计,该估计优于现在广泛使用的周期图方法.然后利用渐进似然函数,建立了广义似然比(GLRT)检测器,该检测器的性能依赖于噪声的未知参数估计的精度,并且得到了检测概率和虚警概率的渐进表达式.通过对含有WSS高斯有色噪声的信号在不同信噪比下的计算机仿真实验分析,结果验证了提出方法的有效性,而且检测性能明显优于原算法.     

Fuzzy clustering of time series in the frequency domain

Traditional and fuzzy cluster analyses are applicable to variables whose values are uncorrelated. Hence, in order to cluster time series data which are usually serially correlated, one needs to extract features from the time series, the values of which are uncorrelated. The periodogram which is an estimator of the spectral density function of a time series is a feature that can be used in the cluster analysis of time series because its ordinates are uncorrelated. Additionally, the normalized periodogram and the logarithm of the normalized periodogram are also features that can be used. In this paper, we consider a fuzzy clustering approach for time series based on the estimated cepstrum. The cepstrum is the spectrum of the logarithm of the spectral density function. We show in our simulation studies for the typical generating processes that have been considered, fuzzy clustering based on the cepstral coefficients performs very well compared to when it is based on other features.     

Generalized adaptive subspace detector for range-Doppler spread target with high resolution radar

A generalized adaptive subspace detector for range-Doppler spread target(RDST-GASD)in the non-Gaussian clutter is derived in this paper.The subspace model of multi-pulse wideband radar target returns is established in the frequency-slow time domain.The clutters are modeled as nonhomogeneous spherically invariant random vectors(SIRVs);that is,the power of the clutter is different from one range cell to another.The clutter covariance matrix is estimated with the secondary data.The constant false alarm rate(CF...     

Multichannel complex maximum entropy (autoregressive) spectral analysis

The Burg reflection-coefficient method for maximum entropy (antoregressive) spectral estimation is generalized to apply to multichannel complex signal. It is shown that all resulting power matrices are positive definite. Preliminary numerical results obtained for a monochromatic signal with noise indicate that the determinants of the power matrices are rapidly reduced as the number of filter coefficients is increased, and that superior spectral resolution can be expected.