采用线性正则域模糊函数的QFM信号参数估计算法输出信噪比分析

摘要

采用线性正则域模糊函数的二次调频(quadratic frequency modulated,QFM)信号参数估计算法简单易解,估计精度较高,误差传递小,在实际应用中有较好的前景.本文对输出信噪比进行了较为深入而详细的分析,推导了输出信噪比与输入信噪比及信号采样点数之间的关系表达式；通过仿真实验比较了在同等条件下和积分广义模糊函数算法(integrated generalized ambiguity function,IGAF)以及多项式相位变换(polynomial-phase transform,PPT)算法的输出信噪比大小,以及达到相同大小输出信噪比所需采样点数.发现该算法的输出信噪比要大于IGAF算法和PPT算法,且达到相同大小的输出信噪比所需采样点数分别是IGAF算法和PPT算法的1/4和1/9,即得到相同大小的输出信噪比时该算法所需的采样点数更少.%The parameter estimation algorithm for QFM signals using ambiguity function based on the linear canonical transform (LCTAF) is simple and has high estimation precision.Its error transfer is also small and has a good application prospect in the project.In this paper,the output signal-to-noise ratio (SNR) of this algorithm is analyzed deeply and derived the relationship between the output SNR and the number of sampling points and input SNR.By simulation experiments we compare the output SNR of LCTAF algorithm,with that of integrated generalized ambiguity function (IGAF) algorithm and polynomial-phase transform (PPT) algorithm under the same condition.And the required numbers of sampling points when the three algorithms achieve the same output SNR are also presented.We find out that the output SNR of our proposed algorithm is bigger than that of IGAF algorithm and PPT algorithm under the same simulation conditions.When achieving the same output SNR,the number of sampling points of LCTAF needed are 1/4 and 1/9 of the IGAF algorithm and the PPT algorithm needed,respectively.That is,the LCTAF algorithm needs fewer sampling points than IGAF algorithm and PPT algorithm.