本论文的核心就是研究不同地声目标识别方法。
The core problem of this thesis is to study the different acoustic signal identification methods.
提出了一种基于灰关联分析的声目标识别算法。
A recognition method based on gray correlation analysis algorithm is proposed through extracting LPC, characteristic from tank, helicopter and car acoustic.
提出一种隐马尔可夫模型和K -均值聚类混合模型的声目标识别方法。
A recognition method based on HMM and K-means cluster is proposed through extracting LPC characteristic from acoustic target.
鉴于声目标识别在民用和军用方面的广泛应用，对声目标进行识别已成为模式识别领域中的研究热点之一。
Due to the wide application of acoustic target recognition in civil and military aspects, it has been a hotspot of study for pattern recognition.
目标识别是战场低空飞行目标声预警技术的核心内容之一。
Passive acoustic recognition for helicopters and cruise missiles is battlefields has attiacted great importance.
本文旨在通过以上研究，能够对声矢量信号中的线谱成分有充分的认识和提取到尽可能多的特征，从而进一步提高舰船目标识别率。
This paper aims to get enough knowledge of line spectrum in acoustic vector signal and extract as more features as possible so as to improve the recognition-rate of targets.
本文旨在通过以上研究，能够对声矢量信号中的线谱成分有充分的认识和提取到尽可能多的特征，从而进一步提高舰船目标识别率。
This paper aims to get enough knowledge of line spectrum in acoustic vector signal and extract as more features as possible so as to improve the recognition-rate of targets.
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