基于小波阈值处理的弱周期脉冲信号混沌检测

A New Method of Chaotic Detection to Weak Periodic Pulse Signal Based on Wavelet Threshold Process

混沌振子检测系统被认为是检测带噪弱信号的有力工具。然而事实证明,上述系统不能保证对噪声充分"免疫",噪声的随机性对检测结果的有效性会产生严重的甚至破坏性的影响。针对上述问题,引入小波阈值处理技术,给出一种基于小波阈值处理检测混沌振子的新型混合检测系统。理论分析与仿真结果均表明,改进方法使得噪声对检测的干扰大幅降低,对信噪比达-23d B的微弱周期脉冲信号实现了成功检测,同时,显著提升了混沌检测的稳定性和可靠性。

In recent years, chaotic oscillator detection system has been considered as a useful method to detect weak signals. However, analyses indicate that the system cannot guarantee the immunity to noises because the randomness of noises has a serious effect on the detection results in many cases. Aiming at this problem, we proposed a new detecting method which can detect Chaotic weak signal accompanied with noise based on wavelet threshold processing. Both the analyses and simulation experiments show that the new method can significantly reduce the noise interferences, and successfully detect weak periodic pulse signals whose signal and noise ratio is -23dB, in the meantime, improve the stability and reliability of the detection of weak signals accompanied with noises.