一种基于ARMA模型的欠定混合快速跳频信号参数盲估计算法

A Blind Parameter Estimation Algorithm of Fast Frequency Hopping Signals for Underdetermined Situation Based on ARMA Model

针对欠定情况下的快速跳频信号的参数估计问题,在基于自回归滑动平均(ARMA)模型的跳变点检测方法的基础上,提出了一种改进的快速跳频信号参数盲估计算法.通过跳周期修正ARMA模型预测点和傅里叶变换分别得到准确的跳变时刻和载频估计,从而实现快速跳频信号的参数估计.实验结果表明,该算法在欠定条件下,当信噪比大于10 dB时,相对现有算法跳变点检测准确率增加了5倍左右,检测准确的概率可以达到90%以上.

Aiming at the parameter estimation of the fast frequency hopping signals for underdetermined situation, an improved blind parameter estimation algorithm was proposed, considering the hopping in- stants detection method based on autoregressive moving average （ARMA） model. The parameter estima- tion of the fast frequency hopping signals was realized by modifying the time-hopping sequence according to the hop duration and Fourier transform. Experiments show the estimation accuracy of the algorithm can reach more than 90% , about five times increasing compared with the existing algorithm for underdeter- mined situation when the signal to noise ratio is greater than 10 dB.