Noise Separation from the Weak Signal Chaotic Detection System

Abstract

The traditional weak signal chaotic detection system still restricts some technical issues in the situation of the signal with noise, such as poor denoising ability and low detection precision. In this paper, we propose a novel weak signal chaotic detection system based on an improved wavelet transform algorithm. First, the traditional wavelet transform algorithm domain variables have been transformed and discretized to eliminate the redundant transform. Then, based on the discrete optimization, the wavelet coefficients have been optimized by threshold compromise strategy. The improved wavelet transform algorithm is applied in the weak signal chaotic detection system. The noise signal after finite discrete processing is treated as a perturbation of cycle power and put into a chaotic system for detecting weak signal under the noise conditions. The simulation experiments show that the proposed improved wavelet transform algorithm has a better denoising effect than the traditional wavelet transform algorithm. Moreover, the improved algorithm shows better accuracy and higher robustness in the weak signal chaotic detection system.

Parameter Estimation of Weak Signal Based on the Steady Attractor of Duffing Oscillator

“…Therefore, even if the noise in the to-be-estimated signal is strong, it disturbs only part of the trajectory without causing any phase transition [11] . Moreover, the variance of the perturbation of the phase trajectory produced by noise is negligible when the system trajectory tends to be infinite [20][21][22] .…”