改进对称共生矩阵的跳频信号盲提取方法

针对短波跳频信号盲检测中的去背景噪声和定频干扰问题,结合信号时频分析与共生矩阵阈值法,提出了一种基于噪声稀疏对称共生矩阵的跳频提取算法.首先对共生矩阵改进,定义了频率、时间方向上的噪声稀疏对称共生矩阵.然后根据频率稀疏共生矩阵估计背景噪声阈值,进而根据阈值从时间稀疏共生矩阵中提取跳频信号.仿真表明,该算法能实现低信噪比下跳频信号的盲提取,背景噪声阈值估计更为准确、稳定,跳频信号的提取效果好,且算法简单、运算量小,易于工程实现.

FH signal extraction using the improved symmetric co-occurrence matrix

Aiming at the problem of removing the background noise and fixed-frequency interference in the blind detection of FH signals from the HF channel, this paper proposes an FH signals extraction algorithm based on the noise-sparse symmetric co-occurrence matrix. Firstly, we define the noise-sparse symmetric co-occurrence matrix in the direction of frequency and time to improve the calculation of the co-occurrence matrix. Secondly, we estimate the noise threshold based on the frequency-sparse symmetric co-occurrence matrix and then extract the FH signals from the time-sparse co-occurrence matrix with the threshold. Simulation results show that the algorithm can realize the blind extraction of the FH signal on the condition of a low SNR. Estimation of the threshold in background noise is more accurate and stable. The performance of FH signal extraction is better and algorithm is simple with less computation and is easy to apply in engineering.