基于时频分析的跳频信号参数估计研究

Research on parameter estimation of frequency-hopping signalsbased on time-frequency analysis

为了解决低信噪比条件下跳频信号参数估计难度大的问题,提出一种基于时频分析方法的跳频信号参数估计方法。首先对跳频信号进行时频变换,获得时频图像,通过能量对消去除定频信号干扰,采用全局阈值法对图像及进行二值化处理,通过形态学滤波消除各类干扰信号的影响。通过对时频脊线的频率跳变时刻数组求解一阶差分方程,得到跳频周期估计值,通过k-means聚类算法估计跳频信号的频率集。仿真实验表明:算法在较低信噪比的情况下,可以获得清晰度较高的时频图像以及精度较高的参数估计值。实测信号的测试验证了算法的实用性。

In order to solve the problem that it is difficult to estimate the parameters of frequency-hopping signals under the condition of a low signal-to-noise ratio,this paper proposes a parameter estimation method of frequency-hopping signals based on time-frequency analysis method.Firstly,time-frequency transform is performed on the frequency-hopping signals to obtain the time-frequency image.The interference of fixed frequency signals is removed by energy cancellation.The global threshold method is used to binarize the image and eliminate the influence of various interference signals by morphological filtering.By solving the first-order difference equation through the frequency-hopping time array of the time-frequency ridge,the estimated value of the frequency-hopping period is obtained,and the frequency set of the frequency-hopping signals is estimated by k-means clustering algorithm.The simulation experiment shows that,under the condition of a low signal-to-noise ratio,the time-frequency image with high definition and parameter estimation with high accuracy can be obtained.The test of the measured signals verifies the practicability of the algorithm.