摘要
采用可见光、红外、SAR、高光谱、电子信号5类传感器对目标进行协同探测,提出了一种基于神经网络与D-S证据理论结合、采用"分层有序"进行目标分类识别的方法,该方法先对目标进行粗分类,然后进行细分类,能准确有效地进行目标的分类识别.
Applying a Multi-sensor, such as optical, infrared, SAR, High-spectrum and electron signal type, to explore the target cooperating, a new approach is proposed based on the Neural Network together with the D-S evidence theory, and ＂orderly quantization＂ is adopted in target recognition. The target is classified extensively and then intensively. The approach can accurately and effectively identify the target.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2009年第3期443-447,共5页
Journal of Xidian University
基金
“863”计划资助(2006AA701304)
关键词
协同探测
分层有序
神经网络
D-S理论
目标识别
cooperating with exploration
orderly quantization
neural network
D-S evidence theory
target recognition
