The conventional expectation maximum (EM) decomposition method combining threshold-based denoising and AIC (Akaike information criterion) is ineffective for eliminating the noisy completely. Moreover, the AIC is less flexible for a small sample target data. To solve this problem, an improved EM waveform decomposition method is proposed, which uses adaptive noise threshold estimation to eliminate background noise and random noise at one time. For the small samples and weak echo target data, the waveform decomposition is performed using EM algorithm collaborated with AICC (Akaike information criterion, corrected). The effectiveness and accuracy of the proposed method are validated based on several sets of measured data.