Estimating the Influence of Modulating Noise on Broad-band Noise-like Signals

V. M. Artyushenko, V. I. Volovach
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Abstract

Mathematical modeling of multidimensional probability distribution density (PDD) under the influence of non-Gaussian fluctuating multiplicative noise is considered, on the basis of which the effect of modulating noise on broad-band noise-like signals is estimated. Cases are considered where a useful signal is exposed only to phase distortions, as well as to simultaneous effects of phase and amplitude distortions, for which multidimensional (N-dimensional) PDD are determined. A special case of determining a two-dimensional PDD of a useful signal is given. It is show that the desired PDD can be determined through one-dimensional PDD when a number of conditions are met. In particular, these conditions may be an increase in dispersion or depth of phase distortion of the signal. It has been show that N-dimensional PDD can also be expressed through PDDs of independent signal samples. It is noted that for a signal distorted by modulating noise, the uncorrelation of its samples means at the same time the independence of the latter. It has been shown that multiplicative noise affects the extraction of a useful signal mainly by changing the characteristics of said signal. It is show that the method of extracting a signal by exceeding a predetermined detection threshold in practically significant cases is the most acceptable. Dependencies of probability of correct and false detection of useful signal on parameters of fluctuating multiplicative noise are obtained. It is noted that when the signal level is significantly exceeded relative to the level of additive noise, multiplicative noise is the main source of distortion of useful information.
估计调制噪声对宽带类噪声信号的影响
考虑了非高斯波动乘性噪声影响下多维概率分布密度(PDD)的数学建模,在此基础上估计了调制噪声对宽带类噪声信号的影响。考虑了有用信号仅暴露于相位失真以及相位和幅度失真的同时影响的情况,其中确定了多维(n维)PDD。给出了确定有用信号二维PDD的一个特例。结果表明,在满足一定条件的情况下,通过一维PDD可以确定所需的PDD。具体地说,这些条件可能是信号的色散增加或相位失真加深。研究表明,n维PDD也可以通过独立信号样本的PDD来表示。值得注意的是,对于被调制噪声扭曲的信号,其样本的不相关同时意味着后者的独立性。研究表明,乘性噪声主要通过改变信号的特性来影响有用信号的提取。结果表明,在实际意义重大的情况下,通过超过预定检测阈值提取信号的方法是最可接受的。得到了有用信号的正误检测概率与波动乘性噪声参数的依赖关系。值得注意的是,当信号电平相对于加性噪声的电平明显超过时,乘性噪声是有用信息失真的主要来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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