脉冲噪声下跳频信号的参数估计研究

发布时间：2019-03-26 20:23

【摘要】：近年来,具有优良的抗干扰性、低截获概率以及可兼容性等诸多优点的跳频信号受到了国内外学者的广泛关注,而且被军事和民用通信等系统广泛采用,有效的参数估计是保证信息准确传输的关键,也是跳频通信研究中的热点和难点。诸多研究表明雷达、地震、生物工程等领域中的杂波干扰或实际噪声均服从?稳定分布,这类分布的概率密度函数具有显著尖峰脉冲状波形和较厚拖尾,且不存在有限的二阶矩和高阶矩。在?稳定分布噪声下,通常的基于高斯模型的信号处理方法会出现性能降低甚至失效的情况。因此,在该类噪声背景下,研究切实可行的跳频信号参数估计方法对于跳频通信的发展具有重要意义。本文针对?稳定分布噪声下的跳频信号参数估计进行了研究,取得的主要成果如下:1.对传统时频分析方法短时傅里叶变换窗宽的选择进行了研究。引入Renyi熵的方法评价时频分析性能的优劣,通过确定最小熵值获得最佳窗宽。结合分数低阶方法,与传统短时傅里叶变换相比,基于Renyi熵的短时傅里叶变换更能准确估计?稳定分布噪声下跳频信号的跳频周期,并且提高了跳变时刻、跳频频率的估计精度。2.对二次型时频分析方法中的交叉项抑制问题进行了研究。针对传统非线性时频分析方法在处理跳频信号时,会出现严重的交叉项和参数估计精度降低等问题,简要分析了交叉项和自项的位置,接着引入RGK时频分析方法,根据信号的不同自适应地选择最优高斯核函数,从而有效抑制远离原点的交叉项并保留原点附近的自项。实验结果表明,该方法具有良好的时频分辨率和参数估计性能。3.对基于广义柯西分布的脉冲噪声抑制方法进行了研究。提出了一种WMGC滤波器,利用最大似然估计理论得到最佳样本值,并结合可靠性加权原则,根据代价函数最小准则求取最佳权系数,从而选取最接近期望值的样本。随后与RGK时频分析方法相结合,提出了WR(WMGC-RGK)方法,并对?稳定分布噪声下的跳频信号进行参数估计。分别与基于分数低阶及Myriad滤波器的时频分析方法进行仿真对比,WR方法在?稳定分布噪声中具有良好的鲁棒性和优良的参数估计性能。
[Abstract]:In recent years, frequency hopping signal, which has many advantages such as good anti-jamming, low probability of intercept and compatibility, has been widely concerned by scholars at home and abroad, and has been widely used in military and civil communication systems. Effective parameter estimation is not only the key to ensure the accurate transmission of information, but also the hot and difficult point in the research of frequency hopping communication. Many studies have shown that clutter interference or actual noise in radar, earthquake, bioengineering and other fields obeys? Stable distribution, the probability density function of this kind of distribution has significant spike pulse shape and thick trailing, and there are no finite second-order moments and higher-order moments. Yes? Under stable distributed noise, the performance of the usual signal processing methods based on Gao Si's model will be degraded or even failed. Therefore, under the background of this kind of noise, it is of great significance for the development of frequency-hopping communication to study feasible parameter estimation methods of frequency-hopping signals. This article is aimed at? The parameter estimation of frequency hopping signal under stable distributed noise is studied. The main results obtained are as follows: 1. The selection of window width of short-time Fourier transform (STFT) based on traditional time-frequency analysis method is studied. The method of Renyi entropy is introduced to evaluate the performance of time-frequency analysis, and the optimal window width is obtained by determining the minimum entropy value. Compared with the traditional short-time Fourier transform (STFT), the short-time Fourier transform (STFT) based on Renyi entropy is better than the traditional short-time Fourier transform (STFT). The frequency hopping period of the frequency hopping signal under stable distributed noise is stable, and the estimation precision of the frequency hopping frequency is improved when the hopping time is improved. 2. The suppression of cross-term in quadratic time-frequency analysis is studied. In order to deal with frequency hopping signals, the traditional non-linear time-frequency analysis method will appear serious cross-term and parameter estimation precision reduction and so on. The position of cross-term and self-term is analyzed briefly, and then RGK time-frequency analysis method is introduced. The optimal Gao Si kernel function is selected adaptively according to the different signals, so that the cross term far away from the origin is effectively suppressed and the self term near the origin is preserved. Experimental results show that the proposed method has good time-frequency resolution and parameter estimation performance. 3. The impulse noise suppression method based on generalized Cauchy distribution is studied. In this paper, a WMGC filter is proposed. The optimal sample value is obtained by using the maximum likelihood estimation theory, and the optimal weight coefficient is obtained according to the minimum criterion of the cost function according to the principle of reliability weighting, so as to select the sample closest to the expected value. Then, combined with the RGK time-frequency analysis method, the WR (WMGC-RGK) method is proposed. The parameters of frequency hopping signals with stable distributed noise are estimated. Compared with the time-frequency analysis method based on fractional low-order and Myriad filter respectively, the WR method is in? Stable distributed noise has good robustness and good parameter estimation performance.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN914.41;TN911.23

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