基于广义二次互相关的低信噪比信号时延估计

针对时延估计精度受噪声影响,导致时延估计不准确的问题,在现有广义二次相关算法的基础上,提出了一种改进的广义二次相关算法,通过将二次相关函数先做指数运算,降低噪声干扰,再将傅里叶逆变换得到的相关函数做高次方运算,达到锐化峰值提高时延正确率的目的。仿真结果表明,信噪比(SNR)在0~10 dB时,改进算法的均方根误差明显优于广义二次相关算法,正确率相比于广义二次相关算法也显著提高,且在更低SNR的情况下仍然具有一定优势。

Time Delay Estimation Algorithm for Low Signal-to-Noise Ratio Signals Based on Generalized Quadratic Cross Correlation

Aiming at the problem that the accuracy of time delay estimation is affected by noise,which leads to inaccuracy of time delay estimation,an improved generalized quadratic correlation algorithm is proposed based on the existing generalized quadratic correlation algorithm.By exponential operation of quadratic correlation function,noise interference is reduced.And then the higher-order operation is performed on the correlation function obtained by the inverse Fourier transform.It can achieve the purpose of sharpening the peak value and improving the correct rate of delay.Simulation results show that the root mean square error of the improved algorithm is significantly better than that of the generalized quadratic correlation algorithm when the Signal-to-Noise Ratio(SNR)is between 0 dB and 10 dB,and the correct rate is also significantly higher than that of the generalized quadratic correlation algorithm.The results also show that the improved algorithm also has certain advantages in the case of lower SNR.