【作者】 金艳；

【导师】 姬红兵；

【作者基本信息】 西安电子科技大学 ， 模式识别与智能系统， 2008， 博士

【摘要】 电子对抗是现代信息对抗领域的重要分支,低截获概率技术是电子对抗系统广泛采用的一种技术,研究低截获概率信号的有效截获和识别方法,对于提高武器装备的作战性能,增强军事对抗的能力具有重要的现实意义和应用价值。本论文在循环平稳理论框架下,针对低截获概率技术中典型的相位编码信号和线性调频信号,开展低截获概率信号的检测和参数估计方法研究,主要内容包括:第一章综述了包括低截获雷达技术和低截获通信技术在内的低截获概率技术的发展概况,重点总结了截获技术中检测和参数估计方法的研究现状,概述了循环平稳理论的研究进展。第二章介绍了循环平稳理论的基础知识,包括循环平稳的基本概念和循环统计量的估计方法及估计性能,对比分析了循环平稳分析法和时频分析法,并阐述了二者之间的关系,说明了在信号检测和参数估计中,循环平稳分析方法抑制噪声与干扰的优势。第三章分析了相位编码信号的循环平稳特性,推导了二相编码信号和四相编码信号的循环自相关函数,深入研究了基于循环自相关函数的单循环检测器,分析了单循环检测器的性能。针对某些非协作条件下缺少与相位编码信号循环频率相关的先验信息等情况,提出了一种基于循环特征的检测方法。该方法可实现较低信噪比下相位编码信号的盲检测。第四章在所推导的相位编码信号循环自相关函数的基础上,分析了延迟自变量对循环自相关函数取值的影响。提出了一种基于循环自相关函数的载频和码片时宽盲估计方法,分析了平稳噪声对该方法性能的影响。该方法在相位编码信号的参数估计中避免了多维搜索,提高了计算效率,为非协作情况下相位编码信号的盲参数估计问题提供了一条有效的解决途径。第五章研究了基于循环自相关函数包络的线性调频信号检测方法,详细分析了该检测方法的性能,并将Dandawate等人所提出的渐近最优χ2检验方案推广到线性调频信号的盲检测中,提出了一种基于循环特征的恒虚警概率检测方法。两种方法均可实现线性调频信号的盲检测。第六章研究了基于循环平稳的线性调频信号相位估计法,推导了所估计相位参数的均方误差近似表达式,分析了该方法的性能。针对循环平稳法的缺点,提出了一种基于循环平稳的线性调频信号参数估计迭代算法,该算法在二阶相位参数的估计中,对迭代初始化和迭代过程采用不同的延迟值,增大了相位参数取值范围,提高了估计精度,降低了误差传递的影响。所提出的迭代算法对线性调频信号相位参数的估计性能明显优于普通的循环平稳法,且与Cramer-Rao界非常接近。第七章对全文进行了总结,并提出了需要进一步研究的问题。更多还原

【Abstract】 Electronic countermeasures are of great importance in the field of information warfare. Low-probability-of-intercept (LPI) techniques are widely utilized in electronic countermeasure systems. Therefore, researches on effective interception and parameter estimation methods of LPI signals have great practical significance and remarkable application value. This dissertation mainly deals with the detection and parameter estimation of phase-coded signals and linear frequency modulated (LFM) signals, which are typical waveforms applied in LPI radar and communication systems, under the framework of cyclostationarity. The main contents are as follows:Chapter 1 introduces the research background and significance of our work firstly. Then a brief review of the advances and the state-of-the-art of LPI signal detection and parameter estimation techniques is presented and the evolution of the cyclostationary theory is summarized.In Chapter 2, the fundamentals of the cyclostationary theory, including the basic concepts of cyclostationarity and the estimation of cyclic statistics, are briefly reviewed. The links as well as the distinctions between cyclostaitionary approaches and time-frequency representations are provided. Finally, the advantages of cyclostaitionary methods in noise and interference suppression are explicated.The cyclostationarity of phase-coded signals is analyzed in Chapter 3, then the explicit formula of the cyclic autocorrelation functions of binary phase-coded signals, as well as those of quaternary phase-coded signals are derived. Single cycle detectors are presented in the form of cyclic autocorrelation function, and their detection performance is analyzed employing the deflection theory. A cyclic feature based detection scheme for phase-coded signals is proposed for non-cooperative cases, which could perform blind detection under rather low signal-to-noise ratios.Based on the cyclic autocorrelation functions derived in the last chapter, the influence of lags on the cyclic autocorrelation is analyzed in Chapter 4. A new cyclic autocorrelation based phase-coded signal blind parameter estimation method is proposed, and the effect of stationary noise on the estimation performance is also provided. The method avoids multi-dimensional searching and has raised the computational efficiency.In Chapter 5, the cyclic autocorrelation envelope based detection method for LFM signals is studied in detail and its performance is evaluated. A cyclic autocorrelation based constant false alarm ratio detection scheme is developed by extending the asymptotically optimal chi-squared test for cyclostationarity, which is proposed by Dandawate et al, to LFM signal detection. Both methods could perform blind detection of LFM signals.The cyclostationary LFM signal phase parameter estimation method is presented in Chapter 6 and its performance is analyzed with the derived approximate mean-square-error analytical expressions of the parameters to be estimated. In order to overcome the drawbacks of the conventional cyclostationary method, an iterative estimation algorithm based on cyclostationarity is proposed. By choosing the lag values for iteration different from those for initialization, the proposed algorithm achieves increased estimation accuracy, reduced error propagation effect and operation over a wider range of phase parameter values. The new iterative algorithm has better performance as compared with the conventional cyclostationary estimation method and is very close to the Cramer-Rao lower Bounds.A summary of the whole dissertation is given in Chapter 7 and a prospect of the issues concerned in this field is also made from the author’s research perspective.更多还原