海杂波背景下的GRNN小目标检测  

GRNN Small Target Detection Based on Sea Clutter

作　　者：卢宁[1] 于才[1] 唐伟[1] 

机构地区：[1]电子科技大学,成都611731

出　　处：《火控雷达技术》2012年第2期4-7,共4页Fire Control Radar Technology

摘　　要：根据海杂波混沌特性,建立了其相空间重构模型,构造了广义回归神经网络(GRNN,Genera-lized Regression Neural Network)目标检测器,并利用加拿大McMaster大学采用IPIX雷达在Dart-mouth地区海域实测带有目标的海杂波数据对此方法进行验证,结果表明:在混沌海杂波背景下GRNN小目标检测法具有良好的预测性和时速性。Based on sea clutter chaotic properties, its phase space reconstruction model and a generalized regres- sion neural network （GRNN） target detector is established which is verified by sea clutter data with small targets measured by IPIX radar of Canadian McMaster University in Dartmouth maritime space. The results show that GRNN small target - detecting method has good predictability and high - speed characteristics at the chaotic sea clutter background.

关 键 词：混沌特性 GRNN 目标检测 

分 类 号：TN957.52[电子电信—信号与信息处理]