| 基于小波包分析的战场被动声目标特征提取 |
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| 引用本文： | 曾番,鹿光,李国宏. 基于小波包分析的战场被动声目标特征提取[J]. 弹箭与制导学报, 2010, 30(2) |
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| 作者姓名： | 曾番 鹿光 李国宏 |
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| 作者单位： | 1. 空军工程大学导弹学院,陕西三原,713800
2. 63615部队,新疆,库尔勒,841000 |
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| 摘 要： | 针对战场环境存在噪声干扰的情况,提出了一种基于小波包分析的声目标特征参数提取方法.该方法将小波包分析和Mel倒谱分析相结合,提高了特征参数的鲁棒性.实验结果表明,在噪声条件下,基于小波包分析的平均识别率比MFCC参数提高6.78%,在信噪比为5dB时,识别率仍能达到94.5%.
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| 关 键 词： | 特征提取 小波包分析 鲁棒性 识别率 |
The Feature Extraction from Battlefield Passive Acoustic Targets Based on Wavelet Packet Analysis |
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| Abstract: | Aimed at noise in battlefield,a method was proposed for feature extraction from acoustic targets based on wavelet packet analysis.The feature parameter combined wavelet packet analysis with Mel-frequency cepstrum analysis,and its robustness was improved.The experiment results show that the recognition rate based on wavelet packet analysis was improved by 6.78% compared with MFCC (DMel-frequency cepstrum coefficients) under noisy environment.When the SNR was 5dB,the recognition rate was up to 94.5%. |
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| Keywords: | feature extraction wavelet packet analysis robust recognition rate |
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