基于ICA算法的卫星TT&C信号的一种新的盲识别算法

在现代通信对抗中,由于电磁环境特别复杂及信号调制方式的多样性,要知道所发射信号的先验知识几乎不可能,这给通信对抗带来极大的困难.为了解决在复杂多信号情况下的这个难题,提出了一种新的盲识别技术,该技术使用独立分量分析(ICA)算法来盲识别原始信号且对所得的结果进行下一步的分别处理.首先介绍了ICA的基本原理:它使用差分负平均信息量的最大化逼近.基于此,ICA的一个目标函数和一种快速的ICA算法在本文中被提出.在深入分析该快速ICA算法的基础上,将其应用于卫星TT&C信号的盲识别上.仿真结果表明:在没有任何先验知识(例如:载波频率,信号带宽和调制方式)的情况下,原始的信号可以被很好地分离出来.这为下面步骤的信号处理建立了一定的基础,比如信号分析和识别,解调信号及证明其收敛和鲁棒性等.

An Improved Blind Separation Algorithm of TT&C Signals of Satellite Based on ICA Algorithm

Due to the complexity of the electromagnetism circumstance and the multiplicity of the signal modulation mode in communication countermeasure, it is impossible to know the prior information of the original signal, which bring great difficulty for communication countermeasure. In order to solve the difficulty of communication countermeasure in circumstance of complex multiple signals, we proposed one new blind reconnaissance technology, which uses the independent component analysis (ICA) to separate the original signals blindly and implement following signal processing to each of the resulting signals. First, the basic principle of the ICA is discussed in this paper. Using maximum approximation of differential Negentropy, an objective function for ICA is introduced and a Fast-ICA algorithm based on maximum Negentropy is presented. Based on analyzing Fast-ICA algorithm deeply, this paper expounds a new method to adopt it in the recognition of TT&C signals of satellite. The simulation results show that original signals can be separated by adopting this method without any priori information (i.e. carrier frequency , signal bandwidth and modulation mode) , which establish a base for following signal processing, such as signal analysis and identity, demodulating and proves its good convergence and robustness.