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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 parameter estimation of fast frequency hopping signal in underdetermined condition, an improved blind algorithm for fast frequency hopping signal parameter estimation is proposed based on the detection method of jump point based on autoregressive moving average (ARMA) model. The jump point correct period and the carrier frequency estimation of ARMA model prediction points and Fourier transform are respectively obtained by the jump period correction to realize the parameter estimation of the fast frequency hopping signal.The experimental results show that under the condition of underdetermined condition, When the ratio is greater than 10 dB, the detection accuracy of the existing transition point of the existing algorithm is increased by about 5 times, and the probability of detection accuracy can reach more than 90%.