基于时频分析的多跳频信号盲检测

为了减小低信噪比下干扰和噪声对跳频信号检测的影响,提出一种基于时频分析的多跳频信号盲检测算法。针对跳频信号、定频信号、高斯白噪声具有的不同时频分布特点,该算法利用短时傅里叶变换得到的时频图构造时频对消比;理论分析得到各信号的时频对消比是不同的,因此将其作为检测统计量,实现高斯白噪声背景下跳频、定频信号的盲检测。仿真结果表明,本文算法具有抗噪声功率不确定性能;与改进型功率谱对消法相比,本文算法在低信噪比环境下,具有更高的跳频信号和定频信号检测概率。此方法也能实现存在定频信号、扫频信号和突发信号干扰的复杂电磁环境中跳频信号盲检测,当信干比为5 dB且跳频信号的检测概率达到100%时,本文算法比改进型功率谱对消法改善信噪比10 dB;在干噪比为0.05 dB时的虚警概率几乎为0。 

Blind detection of multi-frequency hopping signals based on time-frequency analysis

In order to reduce the influence of interferences and noise on frequency hopping signal detection under low signal-to-noise ratio, a blind detection algorithm for multi-frequency hopping signals based on time-frequency analysis is proposed. Considering the different time-frequency distribution characteristics of frequency-hopping signals, fixed-frequency signals, and Gaussian white noise, the time-frequency cancellation ratio is constructed by using the time-frequency map which is acquired from short-time Fourier transform. It is used as the detection statistics because the value of the time-frequency cancellation ratio of each signal is different by the theoretical analysis, and the blind detection of frequency hopping and fixed frequency signals under the background of Gaussian white noise is achieved. The simulation results shown that this algorithm has good robustness to noise power uncertainty, and compared with the improved power spectrum cancellation method, this algorithm has a higher detection probability of multi-frequency hopping and fixed frequency signals in a low SNR environment. This algorithm also can achieve the blind detection of multi-frequency hopping signals in a complex electromagnetic environment where the fixed-frequency signals、sweep signals and burst signals exist as jamming signals, it can improve the signal-to-noise ratio by 10 dB compared with the compared method, when the signal-to-interference ratio is 5 dB and the detection probability of frequency-hopping signals reaches 100%;and the false alarm probability is close to 0 when the interference-to-noise ratio is 0.05 dB.