基于小波变换和ICA的卫星测控信号盲识别算法

Blind Recognition Algorithm for TT&C Signals of Satellite Based on Wavelet Transform and Independent Component Analysis

针对信息对抗中对非合作卫星测控信号识别的问题,提出一种小波变换和独立分量分析相结合的卫星测控信号盲识别算法。首先,基于小波变换去除噪声原理,对混合信号进行去噪处理;然后,采用独立分量分析的方法对去噪后的混合信号进行分离;最后进一步对分离后的测控信号作矢量归一和再去噪处理,得到卫星测控信号的最终估计。Matlab仿真结果表明:该识别算法可以较好地分离卫星测控信号,并且很好地保留了源信号的特征,具有良好的稳定性,收敛速度较快。

A blind sub-carrier recognition algorithm for TT＆C communication is proposed based on wavelet transform and independent component analysis for recognition of TT＆C signals of military TT＆C communication information scout. Firstly, the algorithm denoises the mixed-signals based on the analysis theory of wavelet multi-resolution. Secondly, the mixed signals by independent component analysis are separated. Finally, the separated signals are post-processed, the estimated TT＆C signals of satellite are obtained. Simulation results in Matlab show its better performance and efficiency in the mixed TT＆C signals of satellite recognition, thus proving the good convergence and the robustness.