雷达学报Issue(4)：399-405,7.DOI:10.3724/SP.J.1300.2012.20087
基于神经网络分类的异类传感器目标关联算法
A New Target-correlation Algorithm for Heterogeneous Sensors Based on Neural Network Classification
摘要
Abstract
In the data fusion system composed of radar and infrared sensor installed in high speed of dynamic platform, the system error estimation and target correlation are dependent and are difficult very much. To solve the problem, a new target correlation algorithm based on pattern classification is proposed in the article according to the property of system errors variation. The approach realizes pattern classification by BP neural network. It needn’t estimate the system error and compensate it, and has a tolerance to system error. The experiment shows that the average correct probability for target-correlation in the data fusion between the above two kind of sensors is more than 86%.关键词
数据融合/目标关联/神经网络/分类Key words
Data fusion/Target correlation/Neural network/Classification分类
信息技术与安全科学引用本文复制引用
孟藏珍,袁定波,许稼,彭石宝,王晓军..基于神经网络分类的异类传感器目标关联算法[J].雷达学报,2012,(4):399-405,7.基金项目
国家自然科学基金项目(61102168)资助课题 （61102168）
