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基于连续谱特征提取的被动声纳目标识别技术
引用本文:曾庆军,王菲,黄国建. 基于连续谱特征提取的被动声纳目标识别技术[J]. 上海交通大学学报, 2002, 36(3): 382-386
作者姓名:曾庆军  王菲  黄国建
作者单位:上海交通大学,自动化研究所,上海,200030;华东船舶工业学院,电子与信息系,镇江,212003;华东船舶工业学院,电子与信息系,镇江,212003
基金项目:中国舰船研究院研究所委托项目
摘    要:目标噪声特征提取和目标分类器设计是被动声纳目标识别系统的关键技术 .针对被动声纳目标识别 ,提出了一种新的连续谱特征提取方法 .此外 ,为了训练神经网络目标分类器 ,将遗传算法和 BP算法相结合 ,提出了一种新的自适应遗传 BP算法 .最后 ,对海上实录的三类目标噪声进行了分类识别 .实验结果表明 ,设计的被动声纳目标识别系统具有很好的分类效果

关 键 词:被动声纳目标识别  连续谱  特征提取  自适应遗传BP算法
文章编号:1006-2467(2002)03-0382-05
修稿时间:2001-09-17

Technique of Passive Sonar Target Recognition Based on Continuous Spectrum Feature Extraction
ZENG Qing jun ,],WANG Fei ,HUANG Guo jian. Technique of Passive Sonar Target Recognition Based on Continuous Spectrum Feature Extraction[J]. Journal of Shanghai Jiaotong University, 2002, 36(3): 382-386
Authors:ZENG Qing jun   ]  WANG Fei   HUANG Guo jian
Affiliation:ZENG Qing jun 1,2],WANG Fei 2,HUANG Guo jian 2
Abstract:Feature extraction of targets radiated noise and design of targets classifier are key issues of passive sonar target recognition system. A new feature extraction method of continuous spectrum was proposed, and then a new adaptive genetic backpropagation algorithm was proposed for training neural network target classifier. At last, the classification experiment for three different classes of targets was done, and the results of experiment show that the passive sonar target recognition system designed in the paper has higher correct classification rate.
Keywords:passive sonar target recognition  continuous spectrum  feature extraction  adaptive genetic backpropagation algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
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