基于STFT与SPWVD的跳频参数盲估计算法

Blind parameter estimation algorithm for frequency hopping signals based on STFT and SPWVD

为了降低欠定条件下多网台跳频信号参数盲估计误差,提出一种基于短时傅里叶变换(STFT)与平滑伪WVD分布(SPWVD)相结合的方法.该方法先对信号进行STFT,确定跳变时刻的粗估计范围,再对粗估计范围内的信号进行SPWVD,得到跳变时刻的精确估计,从而估计出跳周期.理论分析与仿真实验结果表明:所提算法在欠定条件下可有效估计出同步正交多网台跳频信号的各参数,与现有的基于时频稀疏性的时频图修正方法相比,在复杂度少量增加的前提下,参数估计误差大幅减小.当信噪比为-4dB时,跳周期、跳变时刻、载频相对估计误差降低了2个数量级,而复杂度只增加了6倍.

To lower the blind parameter estimation errors of multiple frequency hopping（FH）signals in the underdetermined situation,an algorithm based on the combination of short time Fourier transform（STFT）and smoothed pseudo Wigner-Ville distribution（SPWVD）was proposed.The STFT was applied to the signals firstly,and then the rough ranges of the hopping times were obtained.The accurate estimation of the hopping instants was identified by employing SPWVD to the rough ranges,then the hopping period was obtained.Theoretical analysis and experimental results show that this method can effectively estimate the parameters of multiple FH signals in a synchronous orthogonal network in the underdetermined situation.Compared to the existing modification method for time-frequency（TF）pattern of FH signals,even though the computation complexity increases a little,the estimation errors are much better.When the signal noise ratio（SNR）is-4dB,the relative errors of the hopping period,hopping time and frequencies lower two orders of magnitude,while the computation complexity increases only about 6times.