一种同频非合作航天器通信信号的盲源分离算法  

Algorithm of Blind Source Separation for Non-cooperative Spacecraft Communication Signals with Same Carrier Frequencies

作　　者：刘治军[1] 梁宗闯[1] 邱乐德[1] 周业军[1] 齐维孔[1] 

机构地区：[1]中国空间技术研究院通信卫星事业部,北京100094

出　　处：《航天器工程》2015年第6期20-26,共7页Spacecraft Engineering

基　　金：国家高技术研究发展计划(863计划)(2012AA01A504)

摘　　要：针对频谱混叠的同频非合作航天器通信信号分离问题,研究了盲源分离技术,提出一种以立方函数作为非线性函数的盲源分离改进算法。在介绍盲源分离模型的基础上,依据通信信号的亚高斯性,对快速独立分量分析(FastICA)算法的非线性函数作适应性改进,提升了算法的性能。选用8FSK、BPSK、QPSK和频谱混叠的通信信号与单音干扰信号进行混合,仿真并对比分析了4种应用不同非线性函数的FastICA算法。500次的仿真结果表明:应用立方函数的FastICA算法的分离成功率达到100%,平均迭代次数约为25,性能指数均值为0.115 7,具有更优的效能,可很好地解决非合作航天器通信信号的分离问题。To complete the separation of non-cooperative spacecraft communication signal with spectrum aliased,the research of BSS （blind source separation） is carried out. Based on the cubic function as a nonlinear one,the algorithm of BSS is improved. The separation model of BSS is de scribed. The nonlinear function of FastICA （fast independent component analysis） is modified to improve the capability of the algorithm because communication signals are sub-Gaussian signals. Three kinds of common communication signal are mixed with a kind of sine wave interference signal. Several simulations of different algorithms are compared based on different nonlinear functions. The results of 500 simulations show that FastICA algorithm based on cubic function enhances the separation success rate to 100% ,and the average number of iteration times is 25,the performance index is 0. 1157. The cubic function makes the algorithm get the best effect and completes the separation of non-cooperative spacecraft communication signal well.

关 键 词：非合作航天器通信信号 立方函数 盲源分离 频谱混叠 

分 类 号：TN911.4[电子电信—通信与信息系统] V443.1[电子电信—信息与通信工程]