摘要
利用了高阶统计量进行特征提取的方法，着重研究了采用双谱分析的方法提取舰船辐射噪声，给出了双谱矩阵处理的峰值化算法，提取了47维的特征向量并利用BP神经网络对他们进行训练与识别，结果表明，A类目标的正确识别率为83％，B类目标为88％，C类目标为85.19％，D类目标为85.7％。
In order to recognize correctly the signal of ship-radiated noise, the method of feature extraction based on Higher-order statistics is presented. Bispectrum analysis is adopted to the target recognition, and apex arithmetic is given. 47 dimension bispectrum features are extracted from different targets by bispec trum estimation . Based on the features, four types of ships are classified by means of back-propagation ar tificial neural network. The results show that the target recognition rates about four types of ships A,B,C and D are 83.3%,87.8% ,85.2% and 85.71%,respectively.
出处
《青岛大学学报（自然科学版）》
CAS
2004年第4期66-69,共4页
Journal of Qingdao University(Natural Science Edition)
关键词
高阶统计量
舰船辐射噪声
识别
特征提取
Higher-order statistics
ship-radiated noise
target recognition
feature extraction
