摘要
针对无人机空中侦察目标意图识别的问题,提出一种基于径向基神经网络的目标意图识别模型。首先利用雷达收集空中目标相关参数;然后对收集到的数据进行处理并提取特征;最后利用知识库训练好的径向基神经网络对处理后的数据进行模式识别,得到空中目标的意图。案例分析表明,相对于BP神经网络和支持向量机的目标意图识别模型,基于径向基神经网络的空中目标意图识别模型具有更高的准确性。
In order to solve the problem of detection and recognition of air targets by unmanned aerial vehicle(UAV),a targetidentification model is established based on radial basis function(RBF)neural network. First,the relevant parameters of the targetin the air is collected by the radar. Then,the collected data is processed and the feature is extracted. Finally,the radial basis func-tion neural network,which has been trained by the knowledge dataset,is used to identify the pattern of the processed data and getthe intention of air target. The case study shows that the target identification model based on RBF neural network has a higher identi-fication precision as compared with the target identification model based on the BP neural network and SVM.
作者
魏蔚
王公宝
WEI Wei;WANG Gongbao(Department of Basic Courses,Naval University of Engineering,Wuhan 43003)
出处
《舰船电子工程》
2018年第10期37-40,110,共5页
Ship Electronic Engineering
关键词
无人机
目标意图识别
径向基神经网络
BP神经网络
支持向量机
unmanned aerial vehicle(UAV)
recognition of air targets
radial basis function(RBF)neural network
BP neural network
support vector machine(SVM)