基于稀疏重构的跳频信号检测方法

针对复杂电磁环境下跳频信号的检测问题,提出了一种基于稀疏重构的跳频信号检测方法,首先采用近似l0范数算法对含有干扰的跳频信号进行稀疏重构,采用拟牛顿法求解无约束多维最优化问题,然后对得到的时频图的频率分量进行二值形态学滤波以去除干扰和噪声,最后通过统计匹配信号的个数完成信号的检测。同时为提高算法的自适应能力,在选取二值化阈值时采用最大类间方差法。理论分析和仿真实验表明该算法在较低信噪比下仍能克服干扰和噪声并较好地保存各跳,实现对跳频信号的检测。

A Frequency Hopping Signal Detection Method Based on Sparse Reconstruction

In order to detect frequency hopping signals in complex electromagnetic environment, this paper utilizes the approximate l0 norm algorithm for reconstructing the frequency hopping signal with interference according to the sparsity of frequency hopping signal in frequency domain. The unconstrained multi dimensional optimization problem is solved by the quasi Newton method, and the paper utilizes the obtained time frequency map as an image for performing two value morphological filtering to eliminate the interference and noise. Frequency hopping signal is detected by counting the number of matched signals. In view of improving the adaptability of the algorithm, this paper uses the Otsu method in selecting binarization threshold. The theoretical analysis and the simulation show that the algorithm not only can overcome the interference under low SNR condition but also can accomplish signal detection.