电讯技术2015，Vol.55Issue(10)：1074-1078,5.DOI:10.3969/j.issn.1001-893x.2015.10.002
检测海面弱目标的神经网络集成方法
Neural Network Ensemble Approach for Detection of Weak Target in Sea Clutter
摘要
Abstract
It has important values to detect weak targets floating on sea clutter in both military and civilian fields. Weak targets in sea clutter can be detected by radial basis function neural network( RBFNN) predic-tion error method,but detection results are affected by selection training samples. In order to reduce the impact on target detection by samples,the method based on neural network ensemble is proposed to detect weak targets in sea clutter. According to the subnetwork's performance in validation data set,the subnet-work with large difference will be assigned larger weight value. And output of ensembles is constituted of weighted average of subnetwork's output. The method can decrease the impact of the training samples se-lection on target detection effect and enhance the detectability of weak targets embedded in a sea by live re-corded sea returns collected by the McMaster IPIX radar.关键词
海杂波/弱目标检测/神经网络/预测/集成Key words
sea clutter/weak targets detection/neural network/prediction/ensemble分类
信息技术与安全科学引用本文复制引用
刘允峰,索继东,柳晓鸣,苏晓宏..检测海面弱目标的神经网络集成方法[J].电讯技术,2015,55(10):1074-1078,5.基金项目
国家高技术研究发展计划(863计划)项目(2012BAH36B02 ) Foundation Item:The National High Technology Research and Development Program of China(863 Program)(2012BAH36B02) （863计划）
