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 。
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.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2002年第3期382-386,共5页
Journal of Shanghai Jiaotong University
基金
中国舰船研究院研究所委托项目
关键词
自适应遗传BP算法
连续谱
特征提取
被动声纳目标识别技术
passive sonar target recognition
continuous spectrum
feature extraction
adaptive genetic backpropagation algorithm
