重频参差相参脉冲串频率估计算法

Frequency Estimation for Staggered Coherent Pulse Train

研究了重频参差相参脉冲串的频率估计算法。通过脉内相关积累,提高了新序列的信噪比。对新序列的相位差按参差重数抽样平均,减小了等效的相位噪声方差,利用重频参差比解相位模糊,扩大了频偏允许范围,降低了算法的信噪比门限。分析了本算法实现相参频率估计的条件,推导了相应信噪比门限的解析表达式,指出了信噪比门限与信号样本总数、参差重数、参差比之间的关系。仿真结果表明:上述结论是正确的,在满足信噪比门限条件下,频率估计的精度接近相参脉冲串频率估计的克拉美-罗限(CRLB)。

A high accurate frequency estimation algorithm of staggered coherent pulse train is studied.The signal-to-noise ratio（SNR） of a new sequence is enhanced through intrapulse correlation accumulation.Resampling and averaging the phase difference of the sequence according to the number of stagger ratio can reduce the equivalent phase noise.Resolving phase ambiguity through the stagger ratio could enlarge the scope of the frequency difference and decrease the SNR threshold.The requirement for coherent frequency estimation is analyzed and the close-form of the input SNR threshold is derived.Subsequently,we investigate the relationship of the SNR threshold,the total number of samples,the number of stagger ratio and the stagger ratio.Simulation results show that the performance of the proposed algorithm approaches the Cramer-Rao lower bound（CRLB） of the coherent sinusoidal pulse train when the SNR is higher than the SNR threshold.