强混沌和噪声背景下微弱信号的检测

Detection of weak signals in powerful chaotic and noisy background

分析了检测或提取混沌和噪声背景下信号的一些典型方法所存在的局限性,提出以信号的统计独立性来区分混沌和信号特征,使用信息论中的负熵作为统计独立性的判据,进而应用独立分量分析技术,采取逐次分离方法将信号从混沌和噪声中分离出来,从而实现检测的目的。计算机仿真实验表明,这种方法不仅能检测出能量较大的信号,而且对淹没在强混沌和噪声背景下的微弱信号的检测也具有高度的稳定性和可靠性。

Based on the analysis of the limitations of the typical methods to detect or extract the signals in the chaotic and noisy background, a new method was proposed. The statistical independence of the signals measured by the negentropy in the information theory was used to distinguish the chaos and the signals, the independent component analysis technique was used to separate progressively the signals from the chaos and noise, and thus the signals were detected. The computer simulation showed that the proposed method can detect not only the strong signals but also the weak signals in the powerful chaos and noise with great stability and reliability.