基于符号序列信息熵混沌特性的微弱信号检测

Weak signal identification based on chaotic nature of symbol-sequence entropy

利用混沌振子系统的初值敏感性和对噪声免疫的特点检测微弱信号,具有高灵敏度和很好的抗噪性能,其检测的关键在于对混沌振子系统所处状态的识别。针对Duffing振子系统在信号检测领域中的应用,提出了一种基于符号序列信息熵混沌特性的微弱信号检测方法。该方法利用时间序列符号化来捕捉Duffing振子系统时域输出的大尺度特征,应用Shannon信息熵定量计算时间序列中蕴藏的确定性和随机性规律,达到自动识别特定微弱信号的目的。给出了该方法的原理和相应检测程序流程图。实验结果表明,利用该方法可以准确快速地检测出微弱信号,为混沌检测研究的实用化提供了一种有效途径。

Chaotic oscillator is sensitive to initial conditions and immune to noise, these characters are used in weak signal detection. The detection method using chaotic oscillator has good sensitivity and anti-interference capability. The key of the detection method using chaotic oscillator is to identify the chaotic nature state correctly. Based on the analysis of Duffing oscillator in signal detection, a new method for identifying weak signal with Shannon entropy is proposed. The symbol sequence is used to recognize the large-scale characteristics of the chaotic oscillator output in time-domain. The regularity of original data sequence can be determined by Shannon entropy quantitatively, and then the weak signals could be identified accurately and automatically. The principle and program flow chart of the new method are given. Simulation results show that weak periodic signal can be identified precisely and quickly using the proposed method, which provides a practical approach for weak signal detection based on chaotic oscillator.