Research on Weak Signal Detection Performance Based on Chaotic Image Intelligent Recognition

Abstract

The noise immune characteristics of chaotic systems can effectively detect useful signals in the background of strong noise. Aiming at the problem that the state of phase space is judged by human eye observation as the main means and lack of reliable theoretical support, a small sample SVM algorithm for intelligent recognition of chaotic images is proposed in this paper. Firstly, the detection flow of Duffing oscillator under the background of strong acoustic noise while drilling is given, and the weak signal detection models of different state space are given based on phase space and Lyapunov index. The simulation is carried out under different SNR and measured data. Finally, the SVM model is used to intelligently identify chaos and other state space results. The simulation results show that the chaotic system can detect the target signal effectively under different SNR. The minimum SNR is about-80dB and the recognition accuracy of SVM intelligent model is 95%. This conclusion verifies the strong noise immunity of Duffing oscillator system and the effectiveness of SVM model recognition image.