基于Duffing振子检测频率未知微弱信号的新方法

发布时间：2018-02-20 05:05

本文关键词： 微弱信号 Duffing振子噪声遗传算法　出处：《仪器仪表学报》2017年01期 　论文类型：期刊论文

【摘要】：针对现有混沌振子难以检测频率未知微弱信号这一难点,提出利用Duffing振子输出值的方差峰值结合遗传算法检测淹没在强噪声背景中频率未知微弱信号的一种新方法。从分析混沌系统结构参数的阈值入手,讨论了周期策动力的频率、初始相位和噪声对系统运行状态的影响;研究系统输出值方差与系统状态的对应关系,探讨待测信号频率以及与周期策动力之间相位差对状态变量方差和状态转换时间的影响。由此,提出采用具有相位偏移的Duffing振子阵列覆盖全相位,并结合遗传算法,优化求解不同频率输入信号下系统输出值方差的极值,以此得到待测信号频率的方法。该方法解决了现有混沌振子类检测方法必须已知信号频率的限制。实验结果证明了本方法能准确、快速地检测待测信号频率。新方法的状态判定简便、检测精度高、更为灵活、适应性强,为微弱信号的检测提供了新的手段。
[Abstract]:In view of the difficulty of detecting weak signals with unknown frequency by existing chaotic oscillators, A new method of detecting weak signals with unknown frequency in strong noise background by using the peak variance of output value of Duffing oscillator and genetic algorithm is proposed. The frequency of periodic driving force is discussed by analyzing the threshold of structural parameters of chaotic system. The effect of initial phase and noise on the system running state is studied, and the relationship between the system output variance and the system state is studied. The effect of the frequency of the signal to be tested and the phase difference between the signal frequency and the periodic driving force on the variance of state variables and the time of state transition is discussed. Therefore, a Duffing oscillator array with phase offset is proposed to cover all phases, which is combined with genetic algorithm. The extreme value of the system output variance under different frequency input signals is optimized. The method solves the limitation that the existing chaotic oscillator detection methods must know the signal frequency. The experimental results show that the method is accurate. The new method has the advantages of simple state determination, high detection precision, more flexibility and strong adaptability, which provides a new method for weak signal detection.
【作者单位】：华南理工大学电力学院;
【基金】：国家自然科学基金青年科学基金(51505154)项目资助
【分类号】：TN911.23;TP18

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