四阶累积量谱线增强方法的改进仿真研究

为提高自适应谱线增强器跟踪性能,减小高阶累计量的计算量,综合了变步长算法与变符号函数法（ISA）算法的优点,在高阶累积量的能量幂函数变步长极性迭代自适应谱线增强算法的基础上,首次提出了一种计算正弦信号基于高阶累积量变步长ISA算法的迭代自适应谱线增强方法。该方法用输入信号的能量幂函数作变步长来改善跟踪性能,用非输入信号的分段性限幅函数来减小高阶累计量的计算量。仿真结果表明该算法在抑制高斯噪声和非高斯对称分布（拉普拉斯）噪声上优越于基于能量幂函数变步长极性迭代自适应谱线增强算法,能稳定保持信噪比提高3 dB。     

基于高阶累积量不同切片的动态谱线增强算法

为了克服传统的自适应谱线增强器(ALE)抑制高斯噪声效果差的缺点，提出了基于高阶累积量不同切片的自适应动态谱线增强算法，并用水下某运动目标辐射的线谱数据进行了仿真研究。仿真和分析表明：该算法抑制高斯噪声的性能强于ALE算法。因此，本研究有助于提高水下探测系统对微弱信号的检测能力和水下通信能力。     

一种基于高阶累积量的新变步长的自适应谱线增强方法

从减小高阶累积量计算量出发，综合变步长算法和极性算法的优点，提出了基于高阶累积量的能量幂函数型变步长极性迭代自适应动态谱线增强新方法，该方法用输入信号的能量幂函数作变步长来改善跟踪性能，用非输入信号（由输入信号构成的函数）的符号或极性来减小高阶累积量的计算量。仿真表明，该方法具有良好的抑制高斯噪声、增强谱线和跟踪时变信号的性能。     

对角切片谱法分析信号中相位耦合的频率分量

给出了三阶累积量对角切片谱的性质，分析了水中目标辐射信号的特点，并将3阶累积量对角切片谱法应用于提取水下目标辐射信号中相位耦合的频率分量。以水下某目标辐射噪声的实测数据为例，进行了仿真研究。结果表明，该方法在提取水下运动目标辐射信号中的参加相位耦合的频率分量和相位耦合产生的频率分量、抑制环境噪声和非耦合的频率分量等方面的性能优于自相关谱法。     

非高斯有色噪声中谐波恢复的累积量投影方法

本文研究非高斯有色噪声中的谐波恢复问题。首先建立了复数线性非高斯过程的高阶累积量投影定理。应用该定理，由含噪谐波信号的四阶累积量求得非高斯有色噪声的自相关，然后通过求解一个广义特征值问题对矢量空间进行预白化，最后结合噪声子空间方法ＭＵＳＩＣ恢复谐波信号参数。本文方法克服了以往的困难，成功地解决了对称分布非高斯噪声背景下和谐波信号中存在二次相位耦合时的谐波恢复问题。仿真实验验证了本文结论。     

基于符号-最小平均峭度的自适应谱线增强器

从误差信号峭度的性质和误差符号(SE)算法的特点出发,提出了基于符号一最小平均峭度(Sign-LMK)的自适应谱线增强算法。该谱线增强器的结构与基于LMS算法的自适应谱线增强器(ALE)相同,但它是用误差峭度的符号和输入信号作为权向量的更新因子的。仿真结果表明具有计算量小、抑制非高斯噪声和增强谱线性能强、收敛后均方误差小等优点。     

一种基于高阶累积量变步长迭代的自适应谱线增强新方法

依据变步长LMS（Leaset Mean Square)算法能改善自适应谱线增强器（ALE）跟踪性能的特点，提出了基于高阶累积量变步长迭代的自适应谱线增强新方法。用实测水下运动目标辐射噪声数据，对该方法的性能进行了动态仿真研究。仿真表明，该方法具有很好的抑制高斯有色噪声能力的跟踪能力；能有效地增强性调频、对数（或指数）频调信号谱线。因此，在提高水下探测系统功效，识别与检测水下运动目标方面具有一定的指导意义和应用价值。     

基于信噪歪度比的二次相位耦合信号增强新算法

提出了信噪歪度比分析法,在这个分析法中用三阶累积量切片首次定义了信噪歪度比的概念,导出了其理论计算公式。从理论分析可知:当背景噪声为对称分布噪声时,信噪歪度比为无限值;当背景噪声为非对称分布噪声时,在一定条件下,其大于等于输入信噪比。理论分析和仿真结果表明:用三阶累积量切片从非高斯非对称分布的噪声中提取二次相位(动态)耦合信号是有效的,且无需对背景噪声的分布作任何假定。这在工程实践中是非常有意义的。     

基于倒谱的非最小相位FIR系统自适应辨识

本文介绍了一种在高阶谱一维切片的基础上利用倒谱进行非最小相位FIR系统自适应辨识的算法。这一算法具有计算量小，不需要预先假定系统阶次的特点，而且能够自适应地分别辨识出非最小相位FIR系统的最小相位部分和最大相位部分的冲激响应，同时，系统阶次可以在自适应过程中确定。另外由于本算法利用观测信号的高阶级计量进行系统辨识，所以很好地抑制了高斯有色噪声对辨识结果的影响。数值仿真结果证明了本算法的有效性。     

利用希尔伯特变换进行谐波恢复

非高斯有色噪声中具有相位耦合的谐波恢复问题是迄今为止没有得到很好解决的问题，本文基于希尔伯特变换和高阶累积量提出一种新方法：ＨＢＳＴＣＨ－ＳＶＤ－ＴＬＳ。仿真实验表明，该方法不仅次好地解决了非高斯有色噪声中的具有二次相位耦合的谐波恢复问题，而且具有广泛的适用性。     

A higher-order statistics-based adaptive algorithm for lineenhancement

A novel higher order statistics (HOS) based adaptive filtering algorithm for line enhancement is suggested. The enhancement process is achieved by filtering the noisy signal through an adaptive FIR filter. The steady state of the impulse response of this filter is proportional to a selected one-dimensional (1-D) slice of the fourth-order mixed cumulant of the input signal. It is shown that this slice is comprised of noiseless sinusoids if the input signal is comprised of sinusoids embedded in Gaussian noise. Therefore, the algorithm is considered to be a suitable one in processing sinusoids embedded in highly colored Gaussian noise. Simulation results verify the performance of the proposed algorithm     

Higher order cumulants-based least squares for nonminimum-phasesystems identification

A third-order cumulants based adaptive recursive least-squares (CRLS) algorithm for the identification of time-invariant nonminimum phase systems, as well as time-variant nonminimum phase systems, has been successfully developed. As higher order cumulants preserve both the magnitude and the phase information of received signals, they have been considered as powerful signal processing tools for nonminimum phase systems. In this paper, the development of the CRLS algorithm is described and examined. A cost function based on the third-order cumulant and the third-order cross cumulant is defined for the development of the CRLS system identification algorithm. The CRLS algorithm is then applied to different moving average (MA) and autoregressive moving average (ARMA) models. In the case of identifying the parameters of an MA model, a direct application of the CRLS algorithm is adequate. When dealing with an ARMA model, the poles and the zeros are estimated separately. In estimating the zeros of the ARMA model, the construction of a residual time-series sequence for the MA part is required. Simulation results indicate that the CRLS algorithm is capable of identifying nonminimum phase and time-varying systems. In addition, because of the third-order cumulant properties, the CRLS algorithm can suppress Gaussian noise and is capable of providing an unbiased estimate in a noisy environment     

基于输入信号峭度的变步长LMS自适应谱线增强方法

提出了一种基于输入信号峭度的变步长LMS自适应谱线增强方法，该方法以输入信号的峭度为自变量，构造新的步长。该步长对高斯噪声或非高斯噪声均有一定免疫性，同时能快速收敛。最后用实测的水下目标辐射噪声数据和瑞利有色环境噪声进行了仿真，表明该方法有较强的谱线增强能力。     

基于高阶累积量的探地雷达信号处理

本文将高阶累积量方法应用于探地雷达浅层反射信号的处理。由于高阶累积量方法可用于非最小相位的系统辨识,并能抑制加性噪声的影响,故本文基于观测数据的三阶累积量进行探地雷达子波估计,并根据估计的子波进行逆滤波,改善信号的时频分辨率。在此基础上本文提出一种迭代方法,改善子波估计结果,据此得出的逆滤波结果有更好的时间分辨率和信杂比。     

微弱信号非线性检测在随钻电磁波中的应用

在随钻电磁波测井工程中, 随着勘探深度加深, 信号呈现越来越微弱的特性, 有效提取强噪声背景下的微弱电磁波信号对于指导随钻工程勘探具有重要的意义.传统的滤波方法仅滤除带外噪声, 带内噪声不能被很好解决, 针对此问题, 文章设计带外硬件滤波电路和带内基于最小均方算法的可变参数自适应谱线增强(adaptive line enhancer, ALE)算法来构造组合滤波算法.理论分析和仿真研究表明:该组合算法能够提高高动态、低信噪比的微弱电磁波有用信号的估计精度, 有效提高信噪比和抑制工程环境噪声的能力.该组合算法在滤除带外噪声的基础上, 对于带内高斯白噪声抑制能力提高约10 dB, 进一步解决了实际工程问题.     

Image motion estimation algorithms using cumulants

A class of algorithms is presented that estimates the displacement vector from two successive image frames consisting of signal plus noise. In the model, the signals are assumed to be either non-Gaussian or (quasistationary) deterministic; and, via a consistency result for cumulant estimators, the authors unify the stochastic and deterministic signal viewpoints. The noise sources are assumed to be Gaussian (perhaps spatially and temporally correlated) and of unknown covariance. Viewing image motion estimation as a 2D time delay estimation problem, the displacement vector of a moving object is estimated by solving linear equations involving third-order auto-cumulants and cross-cumulants. Additionally, a block-matching algorithm is developed that follows from a cumulant-error optimality criterion. Finally, the displacement vector for each pel is estimated using a recursive algorithm that minimizes a mean 2D fourth-order cumulant criterion. Simulation results are presented and discussed.     

A new hybrid adaptive combination technique for ECG signal enhancement

This paper proposes a new de-noising system technique which is composed of Adaptive line enhancer (ALE) with the discrete wavelet transform (DWT) in order to improve the demerit of the ALE. A new adaptive algorithm which depends mainly on the second order resemblance between a signal and its delayed version is also derived and proposed for the ALE. Unlike the conventional DWT process where an estimation of a specific threshold is taken into account, here the ALE based proposed adaptive algorithm is exploited to enhance the detail coefficients. Therefore, the entire system works well for canceling Gaussian and non-Gaussian noise. Some experiments are carried out on an ECG signal to show the effectiveness of the proposed system. It illustrates from the simulations that the proposed technique demonstrates spectacular results for separating various noise types from the contaminated ECG signal. Finally, the proposed adaptive algorithm is compared with the leaky least mean square algorithm of the bases of mean square error. It is found that the performance of the proposed algorithm provides faster convergence rate and lower steady-state error. Consequently, the overall proposed system model represents a workable solution for ECG signal enhancement.