摘要
针对当前舰船类别识别方法无法高精度辨识舰船类别的难题,设计了一种基于激光技术的舰船类别识别方法。首先采用激光技术采集舰船类别识别的信息,并提取舰船类别识别的特征,然后采用回声状态网络设计舰船类别识别的分类器,实现舰船类别识别,最后进行舰船类别识别的仿真模拟实验,本文方法的舰船类别识别精度超过95%,而且可以抵抗各种噪声的干扰,舰船类别识别的鲁棒性要优于对比模型,实验结果表明本文舰船类别识别方法的优越性。
in view of the problem that ship classification recognition method can not identify ship class at high accuracy, a recognition method of ship class based on laser technology is designed. First of all, laser technology is used to collect the information of ship classification recognition, and the features of ship category recognition are extracted. Then echo state network is used to design classification classifier for ship category recognition, and ship category recognition is realized. Finally, the simulation experiment of ship classification recognition is carried out. The accuracy of ship classification recognition is more than 95%, and it can resist all kinds of noise interference and ship category recognition. Other robustness is better than the contrast model, and the experimental results show the superiority of the ship classification recognition method.
出处
《舰船科学技术》
北大核心
2018年第6X期67-69,共3页
Ship Science and Technology
基金
国家自然科学基金资助课题(11574105)
关键词
舰船类别
识别方法
激光技术
特征向量
分类器
ship classification
recognition method
laser technology
feature vector
classifier
