一种改进的独立分量分析跳频网台分选方法

An Improved Independent Component Analysis Frequency-Hopping Network Station Sorting Method

由于传统的快速独立分量分析算法在复杂环境下实现跳频网台分选时,并未考虑跳频信号瞬时变化快、时频分析复杂等特点,从而导致了算法鲁棒性能低、收敛速度慢、不利于硬件实现。基于此,在快速独立分量分析算法的基础上,对传统的非线性函数做出改进,并将固定点算法的牛顿迭代由二阶收敛转换为五阶收敛,提出了一种适用于跳频信号分选的改进的快速独立分量分析算法。仿真实验表明,该算法的相关系数、性能指标PI值、输出信噪比指数均优于传统的快速独立分量分析算法,且鲁棒性能得到提高、收敛速度加快、运算时间减少60%以上。

In the complex electromagnetic environment,the traditional fast independent component analysis algorithm to achieve frequency-hopping network station sorting does not consider the instantaneous frequency-hopping clipping changes,complex time-frequency analysis and other characteristics,resulting in low robust performance,slow convergence,not conducive to hardware implementation. Therefore,a new method which is suitable for the frequency-hopping signal selected improved fast independent component analysis algorithm based on the fast independent component analysis algorithm. The traditional nonlinear function is improved,and the newton iteration of the fixed point algorithm is converted from second order to fifth order convergence. Simulation results show that the correlation coefficient,PI value and output SNR index of the proposed algorithm are superior to the traditional fast independent component analysis algorithm,and the robustness is improved,the convergence speed is accelerated,and the computation time is reduced by more than 60%.