海杂波背景中小目标检测算法研究

Weak Targets Detection Research under Sea Clutter Background

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.