首页 | 本学科首页   官方微博 | 高级检索  
     

基于神经网络与D-S证据理论的多传感器目标识别技术
引用本文:肖婷婷,张冰. 基于神经网络与D-S证据理论的多传感器目标识别技术[J]. 舰船电子对抗, 2010, 33(2): 90-93
作者姓名:肖婷婷  张冰
作者单位:江苏科技大学,镇江,212003
摘    要:为了满足目标识别的需要,多传感器的数据融合技术已经成为研究的热点。D-S证据理论是多传感器信息融合中最常用的一种处理不确定问题的方法,在基于D-S证据理论的目标识别融合中,基本概率赋值的获取是一个难点。使用神经网络中应用最广泛的BP神经网络来求基本概率赋值,再结合D-S理论进行目标识别。结果表明这种方法可以提高战场目标识别的可靠性,降低识别结果的不确定性。

关 键 词:多传感器  数据融合  目标识别  D-S证据理论  BP神经网络

Multi-sensor Target Recognition Technology Based on Neural Network and D-S Evidence Theory
XIAO Ting-ting,ZHANG Bing. Multi-sensor Target Recognition Technology Based on Neural Network and D-S Evidence Theory[J]. Shipboard Electronic Countermeasure, 2010, 33(2): 90-93
Authors:XIAO Ting-ting  ZHANG Bing
Affiliation:Jiangsu University of Science and Technology;Zhenjiang 212003;China
Abstract:In order to meet the needs of target recognition,the data fusion technology of multi-sensor has become a research hotspot.D-S evidence theory is the most common method to deal with the uncertain problem in multi-sensor data fusion.In the fusion of target recognition based on D-S evidence theory,acquiring the basic probability assignment is a difficulty.This paper uses the BP neural network which is most widely used in neural network to seek the basic probability assignment,then performs the target identific...
Keywords:multi-sensor  data fusion  target identification  D-S evidence theory  BP neural network  
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号