【作者】 黄畅；

【导师】 孙德宝；

【作者基本信息】 华中科技大学 ， 控制理论与控制工程， 2004， 硕士

【摘要】 雷达技术的迅猛发展对雷达侦察系统提出了严峻的挑战。一方面,国内外军用雷达采用的信号形式日益复杂;另一方面,各种电子对抗设备数目急剧增加,电磁信号日趋密集,使雷达侦察系统处于高度密集的信号环境中。因此,信号提取和识别的能力已成为衡量电子对抗技术先进程度的重要标志之一,同时它也是现代雷达技术中急需解决且难度较大的课题之一。本文对低信噪比情况下基于高阶累积量的复杂信号识别研究正是在这一基础上提出来的。本文通过对分数阶Fourier变换和高阶累积量的理论分析研究,把高阶累积量能有效抑制各种高斯噪声的性质和线性调频(LFM)信号在分数阶域的能量聚集性相结合,提出了一种新的时频分析方法——线性调频信号基于高阶累积量的分数阶域的峰度检测。通过仿真,不仅验证了该方法的有效性,还把该方法与原有传统的时频分析方法进行了比较。结果表明,在低信噪比情况下,无论是针对单分量LFM信号还是多分量LFM信号,该方法都可以比传统方法更有效地抑制各种高斯噪声,摆脱交叉项的影响,识别有用信号。因此峰度检测算法可用于低信噪比,多分量LFM信号的复杂情况下,并能有效地抑制各种高斯噪声,更有利于复杂信号的识别。当然,分数阶Fourier域和高阶累积量的研究应用都有待进一步开展。不仅可以应用峰度检测、分数阶Fourier变换对LFM信号的重要特征参数进行估计,还可以将高阶循环累积量的优良性质应用到检测与识别领域。更多还原

【Abstract】 Rapid development of radar technology has put forward an austere challenge to radar reconnaissance system. On the one hand, the forms of both domestic and foreign radar signal become more and more complex. On the other hand, the number of different kinds of electronic reconnaissance equipment increases rapidly, and the electromagnetism signals become more and more dense, so radar reconnaissance system is operating under a highly dense signal environment. Therefore, the ability of distinguishing and identifying the signals has not only become one of the important criterions to estimate the advanced degree of electronic reconnaissance technology, but also become one of the urgent and difficult tasks of modern radar technology. Research on complex signal identification under low signal/noise rate based on high-order cumulant is put forward based on this idea.By carefully analyzing and studying the theory of fractional Fourier transform and high-order cumulant, high-order cumulant has been combined with fractional Fourier transform, because high-order cumulant can effectively inhibit different kinds of Gaussian noise, and the energy of linear-frequency modulate signal congregates in fractional Fourier domain. Therefore, a novel time-frequency analyze method has been put forward in the thesis, that is, the algorithm of LFM signal kurtosis detection based on high-order cumulant in fractional Fourier domain. The results of the simulations have not only proved the validity of the method, but also compared this method with existed traditional time-frequency analysis methods. It has proved that under the circumstance of low signal/noise rate, for either single LFM signal or multi-LFM signal, compared with traditional methods, this method can more effectively inhibit different kinds of Gaussian noise, avoid the influence of cross term and identify useful signal. So the kurtosis detection algorithm can be used in complex circumstance of multi-LFM signal with low signal/noise rate. It can inhibit different kinds of Gaussian noise more effectively and be more suitable for the identification of complex signal.However, the research and application of both fractional Fourier domain and <WP=5>high-order cumulant should be studied further. In the future work, the kurtosis detection and fractional Fourier transform can be used to estimate important characteristic parameters of LFM signal, and some fine characteristics of high-order cyclic cumulant can also be used in the field of signal detection and identification.更多还原