一种混合网台跳频参数盲估计算法

Blind Parameter Estimation of Hybrid Networking Frequency-Hopping

针对低信噪比(SNR)和复杂电磁环境条件下跳频参数估计精度低及算法复杂度高的问题,提出了一种短时傅里叶变换(STFT)和平滑伪魏格纳分布(SPWVD)的组合时频分析方法.该算法首先利用STFT将天线接收信号变换到时频域,并对时频信号进行自适应降噪处理;通过自适应聚类算法进行频率的精估计;提取时频信息并剔除各类干扰,再通过网台分选后得到各类网台跳时粗估计;最后采用SPWVD及修正后的截断门限进行跳变时刻的精估计.仿真结果表明,该算法在混合网台和低SNR条件下,跳频参数估计精度较高,算法复杂度较低,有效解决了实际跳频通信系统存在频率转换时间条件下的参数估计问题。

To solve low accuracy of parameter estimation and high complexity of algorithms in frequency hopping signal under low signal-to-noise ratio(SNR)and complex electromagnetic environment,a new algorithm combined short-time Fourier transform(STFT)with smoothed pseudo Winger-Ville distribution(SPWVD)is proposed.Firstly,the received signals are converted to time-frequency domain by using STFT,and then adaptive noise reduction is used in time-frequency domain.Secondly,the accurate frequency is estimated by adaptive clustering algorithm.Thirdly,the time-frequency information of the signals is extracted and all kinds of interference are eliminated.After the network is sorted,the rough estimation range of the hopping time can be calculated.Finally,SPWVD algorithm and a truncation threshold are used to deal with the rough estimation range,and then a precise frequency estimation is obtained.Simulations show that the parameter estimation of the algorithm has high accuracy and low complexity under the condition of hybrid networking and low SNR.The parameter estimation problem of existing frequency switching time in actual frequency hoppingcommunication system has been effectively solved.