By exploiting wavelet packet transform to analyze signals both in time and frequency space, this paper researches the statistic property of non-Gaussian stationarynoise and its signal structure.
Simulation results show that non-stationarynoise can be identified in time domain and resolution improvement is obvious compared with that of conventional noise detection in frequency domain.
实验表明：非平稳噪声在时域中是可以识别的，与传统的噪声频域检测方法相比，分辨率有明显的改善。
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The shock wave and strong pulse noise, which produced by light rocket launcher, are belong to a nonstationary signal process with a wide frequencies.