Adaptive Wavelet Matched Algorithm Based on Subband Noise

The demand for the detection of objects with low probability of observation is increasingly needed. The reason is that noises always badly affect the measured results. The method of signal detection in low signal to noise ratio (SNR) is widely concerned. To detect the weak signals buried in noises is a fundamental and important problem. It has been found that digital filters are not suitable for processing weak signals in noises, while discrete wavelet transform (DWT) is used to analyze weak digital signal and extract small-features. DTW is a time-frequency analysis technology, which detects the subtle small changes in the signal spectrum. In this paper, we propose a new method of the weak signal acquisition based on DWT. The performance for our method is investigated by detecting the simulating weak signal in white noise. The results show that the DTW is a quite effective method for the extraction features of weak signal and improving the ratio of signal to noise.