共查询到20条相似文献,搜索用时 890 毫秒
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依据零阶统计量理论,给出对数矩过程、对数宽平稳及对数各态遍历的定义,提出一种韧性的归一化自适应时间延迟估计方法(简称NZOSTDE).该算法用FIR滤波器对两个含有脉冲噪声的观测信号建模,利用不存在有限方差的脉冲信号经过对数变换后其各阶矩的存在性和几何功率的概念,在对数域基于最小均方误差(LMS)准则归一化自适应得到FIR滤波器的系数,该系数最大值对应的序号就是时间延迟的估计值.本文提出的新算法克服了基于分数低阶统计量(FLOS)算法的局限性.计算机仿真实验表明,NZOSTDE算法在强脉冲噪声环境下比归一化最小平均P范数时间延迟估计方法(简称NLMPTDE)算法更具有韧性. 相似文献
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基于FLOC的ARMA SαS模型α谱估计方法 总被引:1,自引:0,他引:1
分析了基于分数低阶矩(FLOM)估计ARMA SαS模型参数的不足,根据分数低阶协方差(FLOC)的概念,提出了一种基于分数低阶协方差系数估计ARMA SαS模型参数的方法。在此基础上,给出了ARMA SαS模型的α谱估计。通过对给定ARMA SαS模型的α谱估计、α稳定分布噪声中正弦信号的估计与分辨进行仿真,详细比较了基于FLOM的ARMA SαS模型α谱估计和基于FLOC的ARMA SαS模型α谱估计的性能。结果表明,α值较小时,基于FLOC的ARMA SαS模型α谱估计的性能明显优于基于FLOM的ARMA SαS模型α谱估计。 相似文献
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分数低阶α稳定分布噪声下HB加权自适应时间延迟估计新方法 总被引:1,自引:0,他引:1
针对LMS-HB自适应时间延迟估计方法在分数低阶α稳定分布噪声环境下的退化现象,依据分数低阶统计量理论,提出了基于分散系数最小化的LMP-HB自适应时延估计方法,并进一步提出了不依赖于参数估计的基于非线性变换的HB加权自适应时延估计方法。理论分析和计算机仿真结果表明,新方法在高斯和分数低阶α稳定分布噪声环境下具有良好的韧性。 相似文献
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根据自回归(AR) SαS模型的α谱,分析了基于分数低阶矩(FLOM)法估计AR SαS模型参数的不足.提出了一种基于分数低阶协方差(FLOC)的AR SαS模型参数估计方法,并给出了基于FLOC的AR SαS模型α谱方法.分别对AR SαS模型参数的估计、α稳定分布噪声中单一正弦信号的估计和两个正弦信号的分辨进行了仿真.仿真结果表明,基于FLOC的AR SαS模型α谱估计方法对于不同的α值均具有较好的韧性.特别是在α值较小,即α稳定分布噪声概率密度函数(PDF)拖尾比较严重时,本文所提出的基于FLOC的AR SαS模型α谱估计方法,其性能明显优于基于FLOM的AR SαS模型α谱估计方法. 相似文献
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针对α稳定分布噪声环境下数字通信信号的二阶与高阶循环统计特征显著退化问题,结合分数低阶矩和共变理论对二进制频移键控(Frequency Shift Keying,FSK)信号的分数低阶循环谱公式进行了理论推导,并对2FSK信号在不同混合信噪比、分数阶因子和特征指数条件下的分数低阶循环谱进行了详细的仿真分析.理论和仿真结果表明:2FSK信号分数低阶与二阶的循环谱结构相同,其谱峰对应的循环频率相同,谱峰的幅度值不同,取决于循环谱的阶因子.相对于在低混合信噪比下失效的二阶循环谱,分数低阶循环谱对α稳定分布噪声具有更强的抗干扰性和适用性. 相似文献
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Alpha稳定分布噪声环境下类M估计相关的DOA估计新算法 总被引:1,自引:0,他引:1
提出了一类适用于Alpha稳定分布随机变量的统计量—类M估计相关(MELC),通过构造阵列输出的类M估计相关矩阵,提出了适用于Alpha稳定分布噪声环境下的波达方向(DOA)估计新算法,即MELC-MUSIC算法。仿真实验表明,在Alpha稳定分布噪声环境下,MELC-MUSIC算法在抗噪声特性、多源信号分辨性以及对不同形式信号(圆对称信号或非圆对称信号)的适应性方面获得比基于分数低阶统计量(FLOS)的MUSIC方法更好的估计性能。 相似文献
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利用稳定分布对具有脉冲特性的噪声进行建模,提出了一种新的分数低阶协方差概念,推导了一种基于分数低阶协方差矩阵的波束形成方法,并分析了其旁瓣特性。模拟表明新方法具有更高的信号干扰噪声比及更强的波束形成与旁瓣抑制能力。新算法在高斯和分数低阶稳定分布环境下比传统的算法具有更好的韧性。 相似文献
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The separation of cochannel signals is of interest in communication community. Some algorithms based on constant modulus (CM)
have been previously developed to separate cochannel signals with the assumption of Gaussian channel noise. The mismatches
of noise models between the assumed channel noise and the practical noise may occur. These mismatches will inevitably lead
the performance of cochannel signals separation to degrade. In this paper the alpha-stable distribution is employed as noise
model to simulate impulsive noise occurring in wireless channel. A constant modulus algorithm is proposed to separate the
cochannel signals based on fractional lower-order statistics (FLOS). The convergence of the CM array is analyzed. Numerical
simulations are presented to verify the accuracy of the analytical results. 相似文献
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Li Li Tian-shuang Qiu De-rui Song 《AEUE-International Journal of Electronics and Communications》2013,67(11):947-954
This paper takes the alpha-stable distribution as the noise model and works on the parameter estimation problem of wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system in the impulsive noise environment. In many applications, it is not appropriate to approximate the wideband signal by the narrowband model. Furthermore, the echo signal may be corrupted by the non-Gaussian noise. The conventional algorithms degenerate severely in the impulsive noise environment. Thus, this paper proposes a new wideband signal model and a novel method in wideband bistatic MIMO radar system. It combines the fractional lower order statistics and fractional power spectrum, for suppressing the impulse noise and estimating parameters of the target. Firstly, a new signal array model is proposed under the alpha-stable distribution noise model. Secondly, Doppler stretch and time delay are jointly estimated by peak searching of the FLOS-FPSD. Furthermore, two modified algorithms are proposed for the estimation of the direction-of-departure and direction-of-arrival, including the fractional power spectrum density based on MUSIC algorithm (FLOS-FPSD-MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS-FPSD-ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method. 相似文献
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New methods for time delay estimation and joint estimation of time delay and frequency delay in the presence of impulsive noise are introduced. First, degradation of the conventional approaches based on second-order statistics is shown both theoretically and experimentally. Then, a new class of robust algorithms are developed using the theory of alpha-stable distributions, including the fractional lower order covariance (FLOC) method, which is formulated for the time delay estimation problem and the fractional lower order ambiguity function (FLOAF), which is defined for the joint estimation of time delay and frequency delay. It is shown that these new methods are robust for both Gaussian and non-Gaussian impulsive noise environments. The improved performance is clearly demonstrated through detailed analysis and comprehensive simulations with computer-generated data as well as actual radar and sonar clutter data 相似文献
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This paper takes an Alpha-stable distribution as the noise model to solve the parameter estimation problem of bistatic multiple-input multiple-output (MIMO) radar system in the impulsive noise environment. For a moving target, its echo often contains a time-varying Doppler frequency. Furthermore, the echo signal may be corrupted by a non-Gaussian noise. It causes the conventional algorithms and signal models degenerating severely in this case. Thus, this paper proposes a new signal model and a novel method for parameter estimation in bistatic MIMO radar system in the impulsive noise environment. It combines the fractional lower-order statistics (FLOS) and fractional power spectrum density (FPSD), for suppressing the impulse noise and estimating parameters of the target in fractional Fourier transform domain. Firstly, a new signal array model is constructed based on the \(\alpha \)-stable distribution model. Secondly, Doppler parameters are jointly estimated by peak searching of the FLOS–FPSD. Furthermore, two modified algorithms are proposed for the estimation of direction-of-departure and direction-of-arrival (DOA), including the fractional power spectrum density based on MUSIC algorithm (FLOS–FPSD–MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS–FPSD–ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method. 相似文献
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《Signal Processing, IEEE Transactions on》2006,54(10):3839-3851
Impulsive or heavy-tailed processes with infinite variance appear naturally in a variety of practical problems that include wireless communications, teletraffic, hydrology, geology, and economics. Most signal processing and statistical methods available in the literature have been designed under the assumption that the processes possess finite variance, and they usually break down in the presence of infinite variance. Although methods based on fractional lower-order statistics (FLOS) have proven successful in dealing with infinite variance processes, they fail in general when the noise distribution has very heavy algebraic tails. In this paper, we introduce a new approach to statistical moment characterization which is well defined over all processes with algebraic or lighter tails. Unlike FLOS, these zero-order statistics (ZOS), as we will call them, provide a common ground for the analysis of basically any distribution of practical use known today. Three new parameters, namely the geometric power, the zero-order location and the zero-order dispersion, constitute the foundation of ZOS. They play roles similar to those played by the power, the expected value and the standard deviation, in the theory of second-order processes. We analyze the properties of the new parameters, and derive a ZOS framework for location estimation that gives rise to a novel mode-type estimator with important optimality properties under very impulsive noise. Several simulations are presented to illustrate the potential of ZOS methods. 相似文献
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We address the problem of estimation of the parameters of the recently proposed symmetric, alpha-stable model for impulsive interference. We propose new estimators based on asymptotic extreme value theory, order statistics, and fractional lower order moments, which can be computed fast and are, therefore, suitable for the design of real-time signal processing algorithms. The performance of the new estimators is theoretically evaluated, verified via Monte Carlo simulation, and compared with the performance of maximum-likelihood estimators 相似文献
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