Research on weak signal detection based on wavelet-correlation detection algorithm

The detection of weak signals has a wide range of applications in engineering. In this paper, a combined algorithm of wavelet transform and correlation detection is proposed to address the problems in current detection methods, namely the wavelet-correlation detection algorithm, to detect weak signals. By building a Simulink model on Matlab and implementing simulation through programming, the reliability of the algorithm is verified. The detection performance of the algorithm for weak signals in fixed noise and color noise environments is analyzed, and compared with the cross-correlation detection method. The results show that the wavelet-correlation detection algorithm can distinguish weak signal features from strong noise backgrounds. Taking the 5.2943dB input signal as an example, the wavelet- correlation detection algorithm improves the relative error of amplitude from 1.89% to 0.35%. Signal-to-noise ratio increased by 8.7638dB.