摘要
独立分量分析是近几年来发展起来的一种有效的盲信源分离方法,可以根据输入源信号的基本统计特性,由观测数据进行信号分离,最终恢复出源信号。在深入分析ICA基本理论的基础上,本文将基于负熵最大化的FastICA算法应用于雷达信号分选。仿真试验表明,该算法应用于雷达信号分选可以获得比较好的分离效果。
The Independent Component Analysis （ICA） is an effective method of separating Mind signal sources, which has been developing in recent years. Based on the basic statistical characteristics of input source signals, the signals are separated from the observation data and recovered eventually. After the in-depth analysis of the basic principle of the ICA, the FastICA algorithm based on negentropy maximization is applied to radar signal sorting. The simulation results show that the method is of better separation effect.
出处
《雷达与对抗》
2009年第4期17-20,30,共5页
Radar & ECM
