一种改进的跳频信号参数估计方法

针对在跳频信号跳变时刻和跳变频率估计方面实时性和估计精度无法同时兼顾的问题，提出了一种基于短时傅立叶变换(STFT)和多重信号分类(MUSIC)算法的跳频信号参数估计方法。在建立跳频信号数学模型的基础上，利用STFT选取较大时间窗对整个信号在时域进行粗搜索，生成时频谱图，提取时频脊线从而获得跳变时刻，然后选取较小时间窗在已知跳变时间段利用STFT进行跳变时刻的细估计，并利用MUSIC算法进行频率的精确估计。该方法利用STFT的二次估计，减少了MUSIC搜索范围，从而降低了时间开销。仿真表明该算法的跳变时刻频率估计精度高，实时性能满足参数测量需求。

An improved method for parameter estimation of frequency hopping signals

In order to solve the issues that real time and estimation precision about hopping time and frequency cannot be taken into account simultaneously,a parameter estimation method for frequency hopping signal based on Short-Time Fourier Transform(STFT) and Multiple Signal Classification(MUSIC) algorithm is proposed.On the basis of establishing the mathematical model of frequency hopping signal,using the larger time window,STFT searches the whole signal in the time domain,generates the time-frenquency spectrum map,extracts the time-frequency ridge and obtains the hopping time.Then it selects the smaller time window to estimate the hopping time with the known hopping time,and uses the MUSIC to calculate the accurate estimation of the frequency.The method uses STFT to estimate twice,which reduces the searching scope of MUSIC and the time cost.Simulation results show that this algorithm can estimate hop transition times and the hopping frequencies accurately,and the real-time performance can meet the demand of frequency measurement.