检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]空军工程大学防空反导学院,陕西西安710051
出 处:《信号处理》2014年第1期106-111,共6页Journal of Signal Processing
摘 要:海杂波的非线性预测,是雷达信号处理领域的一个重要研究方向。神经网络具有良好的非线性逼近特性,适用于海杂波时间序列的预测。为了实现强杂波背景中弱小目标的有效检测,本文根据非线性预测思想,给出了基于回归加权径向基函数(radial basis function with regression weight,RBFRW)网络预测误差的海杂波背景中小目标检测方法,并应用此方法仿真了杂波背景中,高分辨力雷达回波信号的检测过程。仿真结果表明:该方法可以在信杂比较低的情况下实现目标信号的有效检测,且检测性能优于应用RBF网络的检测方法,对于复杂杂波背景中小目标检测问题的研究具有一定的价值。Nonlinear forecasting of sea clutter is important field of radar signal processing. Neural network has the advan- tage of approximating the nonlinear function, applies to time series forecasts of sea clutter . With that in mind, this paper proposes weak targets detection based on forecasting error of radial basis function with regression weight neural network un- der sea clutter background, to achieve the result that effectively detect weak target signal under complex clutter back- ground. And, simulates target echo signal detection progress of high resolution radar in this method under background of sea clutter. The simulation results show that this way can effectively detect target signal in relatively low signal to clutter ra- tio, and the detection performance of this method is superior to the detection performance of the method with radial basis function neural network. This method is valuable to the research of weak targets detection under complex clutter back- ground.
关 键 词:线性调频信号 海杂波 回归加权径向基函数网络 预测误差
分 类 号:TN955.1[电子电信—信号与信息处理]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.46