外激励型混沌振子微弱信号检测方法研究
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摘要
在自动化、通信、机械工程等领域,常常需要判断特定规律的微弱信号是否发生,在环境噪声强烈的情况下,利用传统线性滤波的方法会失效,因此一项迫切的任务是寻找新的检测方法。混沌系统具有对初值和参数敏感的特性,这种特性隐藏了作为敏感信号传感的机理,尤其是混沌的非反馈扰动控制体现了对特定信号的敏感和对噪声的免疫特性,从而为微弱信号检测技术提供了新的方法,这种检测方法是从根本上不同于传统微弱信号检测方法的。
本文对混沌振子检测系统中的几个关键问题展开了深入和细致的研究,主要包括混沌振子检测系统的一些特性分析、输出判别、噪声的免疫特性、构成原理这几方面的问题。并借鉴混沌振子检测系统中间歇混沌信号产生的原理,提出了微弱周期信号检测的新方法。
根据检测系统的工作原理,针对混沌检测系统和混沌振子检测系统分别提出一种分类方法。对Duffing-Holmes混沌振子检测系统的特性进行细致的分析,研究了该检测系统中小频率差微弱信号检测和待检测信号频率抖动的问题,得出了小的频率差有利于间歇混沌信号的稳定输出,而在相位连续的条件下,较大的频率抖动也不会影响检测系统的工作。对L-Y混沌振子检测系统的特性进行了研究,给出了该检测系统的一种检测方法。
针对混沌振子检测系统的输出判别问题,在对Duffing-Holmes振子Poincar(?)截面噪声特性分析的基础上,提出了基于Poincar(?)映射的间歇混沌信号判别方法,该方法实现了混沌振子检测系统输出间歇混沌信号的快速判别,并有效抑制了短时噪声的影响。针对这种方法的噪声抑制能力不足的问题,进一步提出了差分Poincar(?)映射判别方法,获得了更好的噪声抑制性能,从而实现了更低信噪比条件下的信号检测。
分析外激励型混沌振子检测系统中噪声的作用方式,指出该类检测系统全局性态对噪声免疫特性分析的必要性,进而将广义胞映射方法引入外激励型混沌振子检测系统的研究。在全局分析的基础上,得出混沌振子检测系统的噪声免疫特性原理,给出利用L-Y混沌振子检测系统实现微弱信号检测的三种构成方法和检测系统中间歇混沌信号产生的条件,并给出外激励型混沌振子检测系统的构成原则。
借鉴混沌振子检测系统中间歇混沌信号的产生原理,利用Poincar(?)截面对信号的重构和对噪声的抑制作用,提出基于外轨周期区域的微弱信号检测方法,并给出了该检测方法的小信号和大信号两种实现方式。利用所提检测方法对信号频率的差分功能,成功地解决了大参数随机共振微弱信号检测的问题。对这种检测方法进行了推广研究,分析了任意Poincar(?)截面构成检测系统的可行性,研究了系统中存在的小混沌区域对该检测方法的影响,研究结果表明大信号方式下存在小尺寸的混沌吸引子,但其对检测系统不构成影响。
In the field of automation, communication, mechanical engineering etc, it is usually needed to judge whether the weak signals with special discipline appear. In the condition of intense environmental noise, the method of conventional linear filtering doesn't work any more. So it is an important task to find new detection methods. The chaotic system has the property of being sensitive to initial values and parameters, which hides the mechanism of sensing sensitive signals, especially the non-feedback perturbing control of chaos shows the sensitivity to special signals and immunity to noise, thus a new method for the weak signal detection technology is provided. This method has fundamental difference from conventional weak signal detection methods.
This thesis performs deep and micromesh work in the key problems of chaotic oscillator detection system, which include analysis, output identification, noise immunity and constructive principle of chaotic oscillator detection system. And a new method of detecting weak periodic signals is proposed using the principle of producing intermittent chaotic signals in the chaotic oscillator detection system as a source of reference.
The classification methods of chaotic detection system and chaotic oscillator detection system are put forward respectively according to the principle of detection system. The property of the Duffing-Holmes chaotic oscillator detection system is analyzed. Then the problem of signal detection with small frequency difference and of frequency jittering of pending signals in this detection system is researched. The result reveals that small frequency difference advantages stable output of intermittent chaotic signals, and a little bigger frequency jittering doesn't have an impact on the detection system. The property of the L-Y chaotic oscillator detection system is researched, and a kind of detection methods of this system is presented.
In allusion to the output identification of chaotic oscillator detection system, the identification method of intermittent chaotic signals based on Poincare mapping is proposed on the basis of analyzing the noise property of Duffing-Holmes oscillator Poincare section. The method makes the rapid identification of intermittent chaotic signals in the chaotic oscillator detection system come true, and restrains effectively the impact of transient noise. In order to solve insufficient ability to restrain noise, a kind of difference Poincare mapping identification methods is further proposed that can achieve better performance of restraining noise. Thus the signal detection under lower Signal-to-Noise level is realized.
How the noise in the external excitation chaotic oscillator detection system works is analyzed. The point that the global behavior of this detection system is necessary to the analysis of noise immunity is presented. Then generalized cell mapping is adopted to analyze the chaotic oscillator detection system. On the basis of global behavior, the noise immunity principle of the chaotic oscillator detection system is raised, and three constructive methods of detecting weak signals and the condition of producing intermittent chaotic signals in the detection system are put forward according to the L-Y chaotic oscillator detection system. Finally, the constructive principle of external excitation chaotic oscillator detection system is presented.
Referring to how to produce intermittent chaotic signals in the chaotic oscillator detection system, a novel weak signal detection method based on outer orbit period region is proposed using the function that the Poincare section reconstructs signals and restrains noise, following which the modes of both large and small signals are given. Taking advantage of the characteristics that the output signal of detection system mentioned has very low frequency, detecting stochastic resonance weak signals with large parameters is successfully solved. Then the new method is further researched to analyze the feasibility that any Poincare section constructs detection system. And the effect the small chaotic area has on the detection method is also studied, the result of which indicates that small size chaotic attractor exists in the mode of large signal, but doesn't influence the detection system.
本文对混沌振子检测系统中的几个关键问题展开了深入和细致的研究,主要包括混沌振子检测系统的一些特性分析、输出判别、噪声的免疫特性、构成原理这几方面的问题。并借鉴混沌振子检测系统中间歇混沌信号产生的原理,提出了微弱周期信号检测的新方法。
根据检测系统的工作原理,针对混沌检测系统和混沌振子检测系统分别提出一种分类方法。对Duffing-Holmes混沌振子检测系统的特性进行细致的分析,研究了该检测系统中小频率差微弱信号检测和待检测信号频率抖动的问题,得出了小的频率差有利于间歇混沌信号的稳定输出,而在相位连续的条件下,较大的频率抖动也不会影响检测系统的工作。对L-Y混沌振子检测系统的特性进行了研究,给出了该检测系统的一种检测方法。
针对混沌振子检测系统的输出判别问题,在对Duffing-Holmes振子Poincar(?)截面噪声特性分析的基础上,提出了基于Poincar(?)映射的间歇混沌信号判别方法,该方法实现了混沌振子检测系统输出间歇混沌信号的快速判别,并有效抑制了短时噪声的影响。针对这种方法的噪声抑制能力不足的问题,进一步提出了差分Poincar(?)映射判别方法,获得了更好的噪声抑制性能,从而实现了更低信噪比条件下的信号检测。
分析外激励型混沌振子检测系统中噪声的作用方式,指出该类检测系统全局性态对噪声免疫特性分析的必要性,进而将广义胞映射方法引入外激励型混沌振子检测系统的研究。在全局分析的基础上,得出混沌振子检测系统的噪声免疫特性原理,给出利用L-Y混沌振子检测系统实现微弱信号检测的三种构成方法和检测系统中间歇混沌信号产生的条件,并给出外激励型混沌振子检测系统的构成原则。
借鉴混沌振子检测系统中间歇混沌信号的产生原理,利用Poincar(?)截面对信号的重构和对噪声的抑制作用,提出基于外轨周期区域的微弱信号检测方法,并给出了该检测方法的小信号和大信号两种实现方式。利用所提检测方法对信号频率的差分功能,成功地解决了大参数随机共振微弱信号检测的问题。对这种检测方法进行了推广研究,分析了任意Poincar(?)截面构成检测系统的可行性,研究了系统中存在的小混沌区域对该检测方法的影响,研究结果表明大信号方式下存在小尺寸的混沌吸引子,但其对检测系统不构成影响。
In the field of automation, communication, mechanical engineering etc, it is usually needed to judge whether the weak signals with special discipline appear. In the condition of intense environmental noise, the method of conventional linear filtering doesn't work any more. So it is an important task to find new detection methods. The chaotic system has the property of being sensitive to initial values and parameters, which hides the mechanism of sensing sensitive signals, especially the non-feedback perturbing control of chaos shows the sensitivity to special signals and immunity to noise, thus a new method for the weak signal detection technology is provided. This method has fundamental difference from conventional weak signal detection methods.
This thesis performs deep and micromesh work in the key problems of chaotic oscillator detection system, which include analysis, output identification, noise immunity and constructive principle of chaotic oscillator detection system. And a new method of detecting weak periodic signals is proposed using the principle of producing intermittent chaotic signals in the chaotic oscillator detection system as a source of reference.
The classification methods of chaotic detection system and chaotic oscillator detection system are put forward respectively according to the principle of detection system. The property of the Duffing-Holmes chaotic oscillator detection system is analyzed. Then the problem of signal detection with small frequency difference and of frequency jittering of pending signals in this detection system is researched. The result reveals that small frequency difference advantages stable output of intermittent chaotic signals, and a little bigger frequency jittering doesn't have an impact on the detection system. The property of the L-Y chaotic oscillator detection system is researched, and a kind of detection methods of this system is presented.
In allusion to the output identification of chaotic oscillator detection system, the identification method of intermittent chaotic signals based on Poincare mapping is proposed on the basis of analyzing the noise property of Duffing-Holmes oscillator Poincare section. The method makes the rapid identification of intermittent chaotic signals in the chaotic oscillator detection system come true, and restrains effectively the impact of transient noise. In order to solve insufficient ability to restrain noise, a kind of difference Poincare mapping identification methods is further proposed that can achieve better performance of restraining noise. Thus the signal detection under lower Signal-to-Noise level is realized.
How the noise in the external excitation chaotic oscillator detection system works is analyzed. The point that the global behavior of this detection system is necessary to the analysis of noise immunity is presented. Then generalized cell mapping is adopted to analyze the chaotic oscillator detection system. On the basis of global behavior, the noise immunity principle of the chaotic oscillator detection system is raised, and three constructive methods of detecting weak signals and the condition of producing intermittent chaotic signals in the detection system are put forward according to the L-Y chaotic oscillator detection system. Finally, the constructive principle of external excitation chaotic oscillator detection system is presented.
Referring to how to produce intermittent chaotic signals in the chaotic oscillator detection system, a novel weak signal detection method based on outer orbit period region is proposed using the function that the Poincare section reconstructs signals and restrains noise, following which the modes of both large and small signals are given. Taking advantage of the characteristics that the output signal of detection system mentioned has very low frequency, detecting stochastic resonance weak signals with large parameters is successfully solved. Then the new method is further researched to analyze the feasibility that any Poincare section constructs detection system. And the effect the small chaotic area has on the detection method is also studied, the result of which indicates that small size chaotic attractor exists in the mode of large signal, but doesn't influence the detection system.
引文
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