基于混沌与高阶累积量的微弱信号检测

Detection of weak sine signals based on chaotic and higher oder cumulants

针对微弱信号幅值很小,常被噪声淹没,而传统去噪方法效果并不理想,研究基于混沌与高阶累积量的微弱正弦信号检测方法,建立仿真模型,并将最大李雅普诺夫Lyapunov指数作为判断混沌系统相变的量化依据,自动识别混沌系统的临界状态,从而准确确定系统的策动力临界阈值。仿真实验表明该方法能有效检测出淹没在高斯噪声中的微弱正弦信号,检测信噪比为-37 dB时,幅度检测相对误差为1.9%。该方法幅度检测门限低,具有广泛应用前景。

A weak signal is difficult to detect because its magnitude is small and it is often submerged in noise,and it is removed ideally by traditional methods. To this problem, a chaotic detection method for weak sine signals based on the chaotic and higher oder cumulants is given.The simulated model is established.Moreover,the proposed method uses Lyapunov expo- nent as the judgment criterion of chaotic dynamics.It can automatically recognize the critical state between the chaotic motion and the periodic motion and give the exact threshold value.Simulation results show that the proposed method can detect weak sine signals in strong noise,when SNR is -37dB, the relative error of amplitude detection is approximately 1.9%.This method also has characteristic of low amplitude detection threshold. Therefore, it will have very good future in applications.