基于独立成分分析的混合LFM信号检测

混合LFM信号广泛存在于实际信号环境巾，对其检测极其重要。对有严重交叉项的混合LFM信号的检测十分困难，因此提出了一种基于独立成分分析的混合LFM信号检测法。通过盲源分离提取各独立成分，利用时频分布矩阵的联合对角化法抑制交叉项，再由各成分信号自项求和重构Wigner-Ville分布，采用Wigner-Hough检测各LFM成分。分析了Wigner-Hough变换输入信噪比和输出信噪比的关系，仿真验证了算法的有效性，得出随着样本点数的增加，在低信噪比条件下，能获得好的检测性能的结论：

Mixed LFM Signal Detection Based on Independent Component Analysis

Mixed LFM signal is everywhere in signal environments in practice, it is important to detect it for electronic intelligence. The cross-terms of Wigner-Ville distribution resulting from mixed signals reduce its resolution. A new method of eliminating the cross-terms based on independent component analysis was presented. The independent signal components were extracted via blind source separation. The cross-terms were reduced significantly based on joint diagonalisation of the time-frequency distribution matrices. The reconstructed Wigner-Ville distribution has good resolution. Each LFM signal components were detected from mixed signals using Wigner-Hough transform. The relation between input SNR and output SNR was computed. The simulation results showed that the new approach improved detection performance and WHT could enhance the output SNR when sampling number was increased.