CAJ | 학술논문

水下环境噪声对被动声呐目标的分类识别影响显著，为了提高水声信号识别系统对环境噪声的鲁棒性，采用提升小波变换方法提取MFCC特征，对水下被动声呐目标进行分类和识别。仿真实验表明，与传统MFCC和小波变换的MFCC相比，在信噪比相近的情况下，提升小波变换方法提取MFCC具有识别率较高、对噪声鲁棒性较好的显著优点。
수하배경조성대피동성눌목표적분류식별영향현저，위료제고수성신호식별계통대배경조성적로봉성，채용제승소파변환방법제취MFCC특정，대수하피동성눌목표진행분류화식별。방진실험표명，여전통MFCC화소파변환적MFCC상비，재신조비상근적정황하，제승소파변환방법제취MFCC구유식별솔교고、대조성로봉성교호적현저우점。
The underwater noise could badly affect the results of passive sonar classification and target recognition. In order to improve the robustness of underwater acoustic signal identification system against environmental noise, a new MFCC feature extraction method based on lifting wavelet transform is proposed. Experimental results show that, compared with the traditional MFCC, the wavelet transform MFCC method for underwater acoustic signal classification and identification works better under the same SNR, which significantly improves the robustness against noise.