摘要
首先介绍了混沌的基本特性,然后利用混沌时间序列对RBF(Radial Basis Function)神经网络进行训练,用训练好的神经网络预测未来的混沌序列的值,最后分别对淹没在混沌杂波及混沌杂波加一定强度的白噪声中的目标进行检测。仿真结果表明,这种方法具有较好的目标检测能力。
The basic characteristics of chaos are presented in this paper at first. Then the RBF neural network is trained using chaos time series, and the future chaos time series are predicted with it. Finally, the targets which are submerged in chaos clutter and in the chaos clutter mixed with a certain intensity of white noise are detected respectively. Simulation results indicate that this method is effective in target detection.
出处
《雷达科学与技术》
2005年第6期327-331,共5页
Radar Science and Technology
