【作者】 胡文；

【导师】 刘中；

【作者基本信息】 南京理工大学 ， 通信与信息系统， 2008， 博士

【摘要】 宽带信号具有良好的距离分辨率、电磁兼容性、抗干扰性能、较高的穿透能力和低截获特性,因此自上世纪60年代以来,在雷达和通信等诸多领域得到了广泛的应用。人们在宽带信号产生、分析与处理等方面取得了一系列有价值的成果;但是,随着新理论和新技术的问世,有关宽带信号研究的新成果也在不断的涌现。混沌信号是由确定性系统产生的伪随机信号,具有易于产生和控制等特点,在宽带和超宽带领域中引起了人们的极大关注。本文就是根据混沌理论的发展,研究基于混沌的宽带/超宽带信号的产生、分析和处理技术。本文的主要工作和贡献可以归纳如下:1.新型混沌信号源和实现研究了混沌二相码序列驱动Colpitts电路实现的混沌系统,提出了由数字电路和模拟电路混合实现的混沌信号产生系统。数字部分产生脉冲信号驱动模拟部分直接产生符合要求的混沌信号;模拟部分又分为振荡器和滤波器两部分,由滤波器控制混沌信号的频谱范围。数值仿真和电路实验表明本文提出的混沌源不仅具有可控的信号频谱,也易于控制和同步。在模拟系统与数字激励之间实现广义同步时,可以用较低时钟频率的数字部分控制产生较高频率的混沌信号。2.混沌信号时频分析算法时间尺度信号计算是进行时频分析的核心运算。对混沌信号,我们首先揭示了混沌时间尺度信号与混沌系统参数之间的关系,然后提出了基于混沌同步的时间尺度混沌信号产生技术,最后发展了宽带混沌信号的模糊函数计算算法。在时间尺度混沌信号产生技术研究中,根据混沌系统是自治的还是非自治的,分别利用脉冲同步和广义同步理论,给出相应的产生技术。在提出的模糊函数计算算法方面,可采用模拟一数字混合结构实现模糊函数计算,为混沌信号分析和雷达应用提供了新手段。3.混沌信号半盲提取与分离提出了基于混沌同步的线性混合混沌信号的半盲提取和分离技术。在混沌信号提取方面,将提取矢量的估计问题转化为混沌系统输出函数参数的估计问题,然后构造基于同步的参数估计方法来提取混沌信号。在混沌信号分离方面,将信道和多个子系统看作一个整体系统,信道混叠参数变为未知的系统参数,然后构造基于同步的参数估计方法,从而分离混沌信号。基于同步的混沌信号分离技术充分利用了每个混沌源信号的产生信息,增强了分离技术的鲁棒性,在信噪比为0dB时仍然有效工作。混沌信号分离技术可应用于降低多用户通信和雷达系统中发射机之间的相互干扰,也可提高混沌信号雷达系统的多目标性能和抗多径干扰能力。更多还原

【Abstract】 Wideband signals have a lot of performance advantages in radar and communication applications, such as high range-resolution, good electromagnetic compatibility, anti-jamming ability, and low-interception probablity. Since 1960, much attention has been taken on the signal research and generated great advances on signal generation, analyses and processing. With the advance on the new theroy and techniques, the new results appear as sequal. Chaotic signal, generated by deterministic systems, can be easily implemented by a simple circuit and controlled to the desired states. Since its founding, the singal has attaracted wide interests in applications. With the development of chaotic theory and appeal in applications, this dissertation mainly studies the generation, analysis and processing of chaotic signals.Main results are concluded as follows:1. New generating system and implementation of chaotic sourcesA Clopitts circuit drived by a chaotic binary code is implemented. Then we propose a chaotic system consisting of digital-analog mixed circuits. The digital circuit provides a pulse-driving signal for the generation of chaotic signals from the analog circuits. The analog circuit consists of the oscillator and the filters. The filters are used to shape the structure of the chaotic singals. The SPICE simulation and circuit implementation show that the new source has controllable spectra and easy to control and synchronize. It is also found that thecircuit can generate high-frequency chaotic signals with low-frequency driving pulse.2. Time-frequency analysis of chaotic signalsTime-scaling signals are key operation in the time-frequency analysis. For chaotic signals, we reveal the relation between the time-scaling and system parameters. With the relation, the time-scaling chaotic signals can be generated with the chaotic generating systems. We apply the generating methods to the analysis of chotic singals and develop the corresponding techniques for calculating ambiguity functions of the chaotic signals. For the generation of the time-scaling singals, we develop the pule-synchaonization-based and generalized-synchronization-based techniques with the corresponding autonomous and non-autonomous systems. The calculation of the amnbiguity functions can be implemented by analog-digital mixed structure and provides new strategy for the analysis processing of chaotic radar signals. 3. Partially-blind extraction and separation of chaotic singalsWe develop the synchronization-based techniques for the extraction and separation of chaotic signals. In the extraction of chaotic signals, we transform the estimation of the extracting vectors into the parameter estimation problem of the chaotic systems. The signal extraction is implemented by a synchronization-based parameter estimation of chaotic systems. In the separation of chaotic signals, we integrate the singal channel and multiple sources into a system. The developed parameter estimation method is used to implement the source separation. The separation technique fully utilizes the information of the chaotic generating systems and enhances the robustness of the separation. It is found that the new technique is still applicable under signal level below 0dB.更多还原