Abstract: The decomposition of waveform data is a key step in waveform analysis. Traditional wave-form decomposition methods cannot detect overlapped sub-waveforms and weak sub-waveforms, and cannot appropriately estimate the number of Gaussian components. In this article, we propose a lateral Gaussian decomposition method. A waveform is smoothed after removing the background noise. We divide the detected waves into different types of waveforms, and estimate their initial parameters with different methods, then progressively laterally decompose waveform until all the Gaussian components are decided. After removing invalid components, we usethe Levenberg-Marquardt method to further optimize the parameters. Experiments show that this new method can effectively detect different kinds of complicated waveforms; demonstrating both robustness and efficiency.